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Provides market research and investment data covering stocks, ETFs, commodities, crypto, forex, analyst ratings, news, earnings, dividends, and economic events.
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get_ai_stock_analysis
TipRanks AI Stock Analysis â the 0-100 AI score for one or more stocks.
Six frontier models (OpenAI, Anthropic, Gemini, xAI, DeepSeek, Perplexity)
research each covered stock independently. Every model returns its own
0-100 score, rating (outperform / neutral / underperform), price target,
and a weighted factor breakdown across financial performance, technical
analysis, valuation, earnings call and corporate events.
Use for: "what's the AI score for NVDA", "AI rating on my watchlist",
"compare the AI scores of AAPL, MSFT and NVDA", "why do the models
disagree on Tesla".
Pass every symbol in one call â a multi-ticker call returns one compact row
per ticker, which is what a watchlist or ranking question needs. A single
ticker also returns every model's score with its factor breakdown plus the
bull and bear key points.
This is NOT the Smart Score (1-10, eight quantitative factors). It is a
separate system, and the two routinely disagree by design.
`ai_score` is the headline score and matches the AI Stock Analysis page;
`consensus` holds the cross-model average, the high and low scoring models,
and the split of rating labels. `upside_pct` is the model's price target
against the current price. `as_of` is when the report was generated â
reports regenerate on new earnings or a significant price move, so an older
date means nothing material has changed since.
Coverage is a subset of the stock universe and excludes ETFs. Symbols with
no report at all come back under `not_covered`; symbols that are covered but
lack a report from the requested `provider` come back separately under
`no_report_from_provider`, each listing the models that did score them â so
a missing provider is never reported as "this stock has no AI analysis".
Args:
tickers: Comma-separated tickers (e.g. 'AAPL' or 'AAPL,MSFT'), max 25.
provider: Optional single provider to report on. Omit for the
headline score that matches the website.
detail: 'consensus' (default) or 'full' to add each model's written
reasoning. Ignored on multi-ticker calls.
Returns JSON: {stocks: [{ticker, company, ai_score, rating,
headline_model, price, price_target, upside_pct, as_of, reflects,
consensus: {models, avg_score, score_high, score_low, ratings_split,
avg_price_target, avg_upside_pct, reports_dated}, providers: [...],
key_points: [...]}], not_covered: [...],
no_report_from_provider: [{ticker, covered_by}]}.
`consensus.reports_dated` appears only when the models did not all run on
the same date; `as_of` is always the headline report's own date.
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{'type': 'object', 'title': 'get_ai_stock_analysisArguments', 'required': ['tickers'], 'properties': {'detail': {'enum': ['consensus', 'full'], 'type': 'string', 'title': 'Detail', 'default': 'consensus', 'description': "'consensus' (default) returns each model's score and factor breakdown; 'full' adds each model's written reasoning. Ignored on multi-ticker calls."}, 'tickers': {'anyOf': [{'type': 'string'}, {'type': 'array', 'items': {'type': 'string'}}], 'title': 'Tickers', 'description': "Comma-separated tickers (e.g. 'AAPL' or 'AAPL,MSFT,NVDA'), up to 25"}, 'provider': {'anyOf': [{'enum': ['OpenAI', 'Anthropic', 'Gemini', 'xAI', 'DeepSeek', 'PerPlexity'], 'type': 'string'}, {'type': 'null'}], 'title': 'Provider', 'default': None, 'description': 'Optional single AI provider to report on. Map what the user said to the provider: Claude is Anthropic, ChatGPT/GPT is OpenAI, Grok is xAI, Sonar is PerPlexity. Omit for the headline score that matches the website.'}}}
get_all_commodities_quotes
Returns real-time quotes for all commodities in a single request.
Each row carries the commodity's display name and a changePercentage derived
from price and change, alongside the raw price, change and volume. Use the
name given in the response â several symbols are non-mnemonic (HEUSX is Lean
Hogs, SBUSX is Sugar, ZSUSX is Soybeans).
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{'type': 'object', 'title': 'get_all_commodities_quotesArguments', 'properties': {}}
get_all_crypto_quotes
Real-time crypto quotes: the largest coins, each with a display name.
The feed carries 4,771 coins in alphabetical order, which is far more than one
response can hold â so this returns `limit` of them ordered by market
capitalisation, largest first, and the response states how many were left out.
Pass `symbols` for specific coins, or call get_crypto_quote for a single one.
Read `note` before summarising: it says how many coins the slice covers out of
how many exist, so a "top coins" answer is not mistaken for the whole market.
`volume` on a crypto row is the source venue's own figure and is not a common
unit across coins â some rows count coins, others quote-currency turnover. It
does not rank the market and coins cannot be compared on it.
Args:
symbols: Comma-separated coins (optional; overrides the ranked slice)
limit: How many ranked coins to return (optional)
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{'type': 'object', 'title': 'get_all_crypto_quotesArguments', 'properties': {'limit': {'type': 'integer', 'title': 'Limit', 'default': 40, 'description': 'How many ranked coins to return (default 40, max 75). Ignored when `symbols` is given.'}, 'symbols': {'type': 'string', 'title': 'Symbols', 'default': '', 'description': "Optional comma-separated coins to return instead of the ranked slice, e.g. 'BTCUSD,ETHUSD'. Bare tickers like 'BTC' resolve to the USD pair."}}}
get_all_forex_quotes
Real-time forex quotes: the most-traded pairs, each with a display name.
The feed carries 1,550 pairs in alphabetical order, which is far more than one
response can hold â so this returns the most prominent `limit` of them (majors
first, then by volume), and the response states how many were left out. Pass
`symbols` for specific pairs, or call get_forex_quote for a single one.
Read `note` before summarising: it says how many pairs the slice covers out of
how many exist, so a "top pairs" answer is not mistaken for the whole market.
`volume` on a forex row is a per-venue tick count, not market turnover â FX is
over-the-counter and most pairs report 0. It does not rank the market.
Args:
symbols: Comma-separated pairs (optional; overrides the ranked slice)
limit: How many ranked pairs to return (optional)
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{'type': 'object', 'title': 'get_all_forex_quotesArguments', 'properties': {'limit': {'type': 'integer', 'title': 'Limit', 'default': 40, 'description': 'How many ranked pairs to return (default 40, max 75). Ignored when `symbols` is given.'}, 'symbols': {'type': 'string', 'title': 'Symbols', 'default': '', 'description': "Optional comma-separated pairs to return instead of the ranked slice, e.g. 'EURUSD,USDJPY'. Slash and dash forms are accepted."}}}
get_analysts_by_firm
List analysts at a given firm (case-insensitive substring match).
Each row: {name, firm, rank, avg_return_1y_pct, covered_tickers_sample,
total_covered}. Results are deduped by analyst name (keeping the best
rank) and sorted by rank ascending.
When `sector` is provided, the per-analyst coverage list is filtered
to tickers in that sector and the row shape becomes {name, firm,
rank, avg_return_1y_pct, sector, covered_tickers}.
Args:
firm: Firm name or fragment (e.g. 'Goldman' matches 'Goldman Sachs').
sector: Optional lowercase sector (e.g. 'technology', 'healthcare').
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{'type': 'object', 'title': 'get_analysts_by_firmArguments', 'required': ['firm'], 'properties': {'firm': {'type': 'string', 'title': 'Firm'}, 'sector': {'type': 'string', 'title': 'Sector', 'default': ''}}}
get_article
Fetch the full text of a single TipRanks article.
Resolve a TipRanks article URL (e.g. from get_latest_news / get_assets_news),
a slug, or a numeric post id to its title, excerpt, full body text
(HTML-stripped, capped at 8000 chars), author, category, date, canonical
URL, and any tagged tickers.
Args:
identifier: Numeric post id, slug, or a tipranks.com article URL.
Returns a JSON object, or {"error": ...} when no matching TipRanks article
exists (e.g. the URL points to an aggregated third-party site, which is not
stored in TipRanks).
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{'type': 'object', 'title': 'get_articleArguments', 'required': ['identifier'], 'properties': {'identifier': {'type': 'string', 'title': 'Identifier', 'description': 'A TipRanks article identifier: the numeric post id, the slug, or a full tipranks.com article URL.'}}}
get_assets_data
Returns key TipRanks stock data for one or more tickers.
Args:
tickers: Ticker symbols â a comma-separated string ("AAPL,MSFT,C") or a
JSON array (["AAPL","MSFT","C"]). Both are accepted.
Returns JSON {"assetsData": [...one compact entry per ticker...]}. This is a
headline summary tuned to stay small enough for a whole portfolio to fit in a
single response. Fields per entry:
- ticker, companyName, sector, stockType, marketCap
- url: canonical TipRanks page for the stock â use as the citation source.
- price: latest close.
- smartScore: TipRanks composite 1-10 (combines the 8 datasets â analyst,
blogger, news, hedge-fund, insider, etc.).
- analystConsensus / bestAnalystConsensus: rating label from ALL covering
analysts vs. the top-performing ones ("Strong Buy".."Strong Sell"); a
divergence between the two is itself a signal.
- priceTarget: average 12-month target. priceTargetUpside: decimal vs.
current price (0.05 = +5%).
- peRatio, dividendYield (decimal).
- newsSentiment, hedgeFundsScore, insiderScore: 0-1 sentiment signals.
- ytdGainPct, yearlyGainPct: price performance as a percent (12.5 = +12.5%,
3944 = +3944%).
- nextEarningsDate, and daysUntilEarnings (whole days from today â quote this
rather than computing the gap from the date yourself).
Floats are rounded and dates are day-resolution. For deeper per-ticker detail
(full price history, 13F / insider breakdowns, blogger counts, financials)
use the dedicated tools (get_stock_prices, get_hedge_fund_holdings,
get_insider_transactions, get_financials, ...).
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{'type': 'object', 'title': 'get_assets_dataArguments', 'required': ['tickers'], 'properties': {'tickers': {'anyOf': [{'type': 'string'}, {'type': 'array', 'items': {'type': 'string'}}], 'title': 'Tickers'}}}
get_assets_events
Returns upcoming dividend and earnings events for tickers.
Args:
tickers: Comma-separated ticker symbols (e.g. "AAPL,MSFT")
from_date: Optional start date (ISO format, e.g. "2026-03-01")
to_date: Optional end date (ISO format, e.g. "2026-06-01")
Returns: dividend dates, earnings dates, and coupon dates per ticker.
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{'type': 'object', 'title': 'get_assets_eventsArguments', 'required': ['tickers'], 'properties': {'tickers': {'anyOf': [{'type': 'string'}, {'type': 'array', 'items': {'type': 'string'}}], 'title': 'Tickers'}, 'to_date': {'type': 'string', 'title': 'To Date', 'default': ''}, 'from_date': {'type': 'string', 'title': 'From Date', 'default': ''}}}
get_assets_news
Returns recent news articles for tickers, aggregated from many news
sites, each with a sentiment tag and source URL (headlines only â no
article body). For general/market TipRanks news without a specific ticker,
or for an article excerpt, use get_latest_news.
This tool serves the CURRENT news window only: it returns each ticker's most
recent articles, and from_date just trims that recent set. For news from a
specific past date range, use get_latest_news with from_date + to_date,
which searches the full archive.
Args:
tickers: Comma-separated ticker symbols
count: Number of articles to return (default 10)
from_date: Optional 'YYYY-MM-DD' recency floor (filtered on `date`).
Returns JSON: {"assetNewsArticles": [...]}. Each entry:
- ticker, companyName
- sentiment: bucketed signal â one of "VeryPositive", "Positive",
"Neutral", "Negative", "VeryNegative". Derived from TipRanks
news-sentiment classifier on the article text.
- siteName, url, title
- date, addedOn, publishTime, articleTimestamp: redundant date
fields. addedOn is when TipRanks ingested it; publishTime is
the source's stated publication time. Prefer publishTime.
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{'type': 'object', 'title': 'get_assets_newsArguments', 'required': ['tickers'], 'properties': {'count': {'type': 'integer', 'title': 'Count', 'default': 10}, 'tickers': {'anyOf': [{'type': 'string'}, {'type': 'array', 'items': {'type': 'string'}}], 'title': 'Tickers'}, 'from_date': {'type': 'string', 'title': 'From Date', 'default': '', 'description': "Optional recency floor 'YYYY-MM-DD', applied to the recent articles this tool returns. It cannot pull older news into range â\x80\x94 for a past date window use get_latest_news with from_date + to_date."}}}
get_assets_warnings
Returns risk warnings for tickers.
Args:
tickers: Comma-separated ticker symbols
Returns: warning type, date, and detail fields per ticker.
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{'type': 'object', 'title': 'get_assets_warningsArguments', 'required': ['tickers'], 'properties': {'tickers': {'anyOf': [{'type': 'string'}, {'type': 'array', 'items': {'type': 'string'}}], 'title': 'Tickers'}}}
get_best_performing_experts
Returns the best-performing experts ranked by TipRanks success rate and average return.
Args:
expert_type: One of: analyst, insider, hedgeFund, blogger, firm (default: analyst)
num: Number of results (default: 10, max: 25)
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{'type': 'object', 'title': 'get_best_performing_expertsArguments', 'properties': {'num': {'type': 'integer', 'title': 'Num', 'default': 10}, 'expert_type': {'type': 'string', 'title': 'Expert Type', 'default': 'analyst', 'description': 'One of: analyst, insider, hedgeFund, blogger, firm (default: analyst)'}}}
get_blogger_sentiment
Returns the financial-blogger consensus for a stock plus the underlying
blogger articles.
Distinct from get_recent_analyst_ratings (Wall Street analysts) and
get_investor_sentiment (TipRanks crowd positioning).
Args:
ticker: Stock ticker (e.g. 'AAPL')
limit: Max blogger articles to return (default 20, max 50)
Returns JSON: {ticker, company, consensus, articles}.
- consensus: {bullish_pct, bearish_pct, neutral_pct, bullish_count,
bearish_count, neutral_count, score, avg}.
- articles: [{blogger, title, url, site, date}] (newest first).
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{'type': 'object', 'title': 'get_blogger_sentimentArguments', 'required': ['ticker'], 'properties': {'limit': {'type': 'integer', 'title': 'Limit', 'default': 20}, 'ticker': {'type': 'string', 'title': 'Ticker'}}}
get_bulls_bears_summary
Returns the discrete bull and bear key points for stocks â the individual
sentence bullets TipRanks shows on its stock pages, each tagged with a topic.
Args:
tickers: Comma-separated tickers (e.g. 'AAPL,TSLA')
Returns JSON: {"data": [...one entry per ticker...]}. Each entry has:
- ticker, updatedOn
- bullish: list of bullish point sentences
- bearish: list of bearish point sentences
- key_points: list of {sentiment, topic, point} for the full set.
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{'type': 'object', 'title': 'get_bulls_bears_summaryArguments', 'required': ['tickers'], 'properties': {'tickers': {'anyOf': [{'type': 'string'}, {'type': 'array', 'items': {'type': 'string'}}], 'title': 'Tickers'}}}
get_buybacks
Returns share-buyback / stock-repurchase activity in one of two modes:
- CROSS-MARKET (no ticker): latest reported buybacks across all companies,
sorted by dollar amount spent (largest first). Use for 'biggest buybacks',
'top repurchase companies'. A single company may appear multiple times for
different fiscal quarters.
- PER-TICKER (ticker provided): historical quarterly buyback series for one
ticker. Use for 'AAPL buyback history', 'MSFT repurchase trend'.
Args:
ticker: Optional. If provided, returns the per-ticker historical series.
If empty, returns the cross-market list.
limit: Cross-market mode only â max rows (default: 25, max: 100).
page: Cross-market mode only â page number, 1-based (default: 1).
Returns:
Cross-market mode: { totalCount, data: [{ ticker, companyName,
fiscalPeriodEndDate, stockEarningsDate, eps,
marketCapUSD, totalValueSpentToRepurchaseShares,
epsCurrencyTypeCode }] }.
Per-ticker mode: quarterly time series, chart-ready as a bar or
line plot of buyback spend over time â
[{ date, marketCapEndFiscalPeriod,
totalValueSpentToRepurchaseShares,
ratio (decimal â buyback / market cap) }, ...].
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{'type': 'object', 'title': 'get_buybacksArguments', 'properties': {'page': {'type': 'integer', 'title': 'Page', 'default': 1}, 'limit': {'type': 'integer', 'title': 'Limit', 'default': 25}, 'ticker': {'type': 'string', 'title': 'Ticker', 'default': '', 'description': 'Optional. If provided, returns the per-ticker historical buyback series; if omitted, returns the cross-market list.'}}}
get_clinical_trials
Returns the FDA / clinical-trial calendar â upcoming drug approval target
dates and the tickers behind each drug.
Window is fixed at today â 14 days to today + 60 days, sorted by date ascending.
Use for upcoming FDA decisions, PDUFA dates, biotech catalysts.
Returns: { data: [{ targetDate, clinicalTrials: [{ drugName, ticker }] }],
count, window }.
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{'type': 'object', 'title': 'get_clinical_trialsArguments', 'properties': {}}
get_commodity_historical
Daily OHLC price history for a commodity, covering the whole date range you ask for.
Chart-ready: while the range fits in one response, each row is the price feed's
own daily row â {symbol, date, open, high, low, close, volume, change,
changePercent, vwap} â newest first, ordered for direct plotting as a price history.
A range too long to return day by day is aggregated into coarser OHLC bars
rather than cut short. `interval` names which (weekly/monthly/quarterly/yearly),
each bar spans `date` to `endDate`, and a bar's high/low are that period's real
extremes. Aggregated bars carry the same fields except `vwap`, which the feed
defines per session only. Re-request a narrower from_date/to_date for daily rows.
`summary` always describes the FULL requested window, computed from the daily
data: its first and last close with dates, its high and low with dates, and the
trailing changes the window reaches back far enough to support. Base any
"starting price", "a year ago" or "period high/low" claim on `summary`, or on a
bar that is actually present.
`summary.windowHigh`/`windowLow` describe THIS window. A quote tool's
yearHigh/yearLow are the feed's trailing range, roughly the past 12-13
months â a different period â so label those as trailing-year figures. For the current level alone, call get_commodity_quote.
Args:
symbol: Commodity symbol (e.g. 'GCUSD' for gold)
from_date: Start date YYYY-MM-DD (optional)
to_date: End date YYYY-MM-DD (optional)
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{'type': 'object', 'title': 'get_commodity_historicalArguments', 'required': ['symbol'], 'properties': {'symbol': {'type': 'string', 'title': 'Symbol', 'description': "Commodity symbol, e.g. 'GCUSD' (gold)."}, 'to_date': {'type': 'string', 'title': 'To Date', 'default': ''}, 'from_date': {'type': 'string', 'title': 'From Date', 'default': ''}}}
get_commodity_quote
Returns the real-time price quote for a specific commodity.
Common symbols: GCUSD (gold), SIUSD (silver), CLUSD (crude oil),
NGUSD (natural gas), HGUSD (copper), PLUSD (platinum).
yearHigh / yearLow are the feed's trailing-year range, roughly the past
12-13 months: call them trailing-year figures. For a year-to-date or
calendar-year change, a dated extreme or an exact 52-week figure use
get_commodity_historical, since the quote does not date its extremes.
Args:
symbol: Commodity symbol (e.g. 'GCUSD' for gold)
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{'type': 'object', 'title': 'get_commodity_quoteArguments', 'required': ['symbol'], 'properties': {'symbol': {'type': 'string', 'title': 'Symbol', 'description': "Commodity symbol, e.g. 'GCUSD' (gold), 'CLUSD' (crude oil)."}}}
get_company_kpis
Returns company-specific operational KPIs: segment revenue, geographic
breakdown, active users/devices, gross margins by type, opex breakdown.
Full history runs back to 2014 and is large, so this returns the most
recent `count` periods per metric by default â pass count=0 for the full
history, or `group` to fetch a single group.
Args:
ticker: Stock ticker (e.g. 'AAPL', 'MSFT')
count: Most-recent periods per metric (default 8, max 40; 0 = full history)
group: Optional single group by slug or title
Returns JSON: {"ticker", "lastUpdated", "groups": [...]}. Each group has
slug, title, and metrics: [{title, slug, unit, series: [{periodEnd, value}]}].
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{'type': 'object', 'title': 'get_company_kpisArguments', 'required': ['ticker'], 'properties': {'count': {'type': 'integer', 'title': 'Count', 'default': 8}, 'group': {'type': 'string', 'title': 'Group', 'default': '', 'description': "Optional single KPI group by slug or title (e.g. 'revenue_geography', 'Revenue by Segment'). Omit for all groups."}, 'ticker': {'type': 'string', 'title': 'Ticker'}}}
get_crypto_historical
Daily OHLC price history for a cryptocurrency, covering the whole date range you ask for.
Chart-ready: while the range fits in one response, each row is the price feed's
own daily row â {symbol, date, open, high, low, close, volume, change,
changePercent, vwap} â newest first, ordered for direct plotting as a price history.
A range too long to return day by day is aggregated into coarser OHLC bars
rather than cut short. `interval` names which (weekly/monthly/quarterly/yearly),
each bar spans `date` to `endDate`, and a bar's high/low are that period's real
extremes. Aggregated bars carry the same fields except `vwap`, which the feed
defines per session only. Re-request a narrower from_date/to_date for daily rows.
`summary` always describes the FULL requested window, computed from the daily
data: its first and last close with dates, its high and low with dates, and the
trailing changes the window reaches back far enough to support. Base any
"starting price", "a year ago" or "period high/low" claim on `summary`, or on a
bar that is actually present.
`summary.windowHigh`/`windowLow` describe THIS window. A quote tool's
yearHigh/yearLow are the feed's trailing range, roughly the past 12-13
months â a different period â so label those as trailing-year figures. For the current level alone, call get_crypto_quote.
Args:
symbol: Cryptocurrency symbol (e.g. 'BTCUSD' for Bitcoin)
from_date: Start date YYYY-MM-DD (optional)
to_date: End date YYYY-MM-DD (optional)
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{'type': 'object', 'title': 'get_crypto_historicalArguments', 'required': ['symbol'], 'properties': {'symbol': {'type': 'string', 'title': 'Symbol', 'description': "Crypto symbol, e.g. 'BTCUSD' (Bitcoin)."}, 'to_date': {'type': 'string', 'title': 'To Date', 'default': ''}, 'from_date': {'type': 'string', 'title': 'From Date', 'default': ''}}}
get_crypto_news
Latest cryptocurrency news â a market-wide feed across all coins (not
filtered to a single asset), ordered newest-first: article headlines,
snippets, and source URLs. Read-only, no side effects.
Use for broad crypto/market headlines. For news about a specific holding
use get_assets_news; for the general (non-crypto) editorial feed use
get_latest_news.
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{'type': 'object', 'title': 'get_crypto_newsArguments', 'properties': {'page': {'type': 'integer', 'title': 'Page', 'default': 0, 'description': '0-indexed page of recent articles (0 = most recent); increase to page further back in time.'}}}
get_crypto_quote
Returns the real-time price quote for a specific cryptocurrency.
Common symbols: BTCUSD (Bitcoin), ETHUSD (Ethereum), SOLUSD (Solana),
BNBUSD (BNB), XRPUSD (XRP), ADAUSD (Cardano), DOGEUSD (Dogecoin).
yearHigh / yearLow are the feed's trailing-year range, roughly the past
12-13 months: call them trailing-year figures. For a year-to-date or
calendar-year change, a dated extreme or an exact 52-week figure use
get_crypto_historical, since the quote does not date its extremes.
Args:
symbol: Cryptocurrency symbol (e.g. 'BTCUSD' for Bitcoin)
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{'type': 'object', 'title': 'get_crypto_quoteArguments', 'required': ['symbol'], 'properties': {'symbol': {'type': 'string', 'title': 'Symbol', 'description': "Crypto symbol, e.g. 'BTCUSD' (Bitcoin), 'ETHUSD' (Ethereum)."}}}
get_dividend_history
Dividend payment history for a ticker. Chart-ready: includes the
current snapshot (yield %, payout ratio, frequency, annualised
payout) plus two time series â a per-payment list
[{ex_date, pay_date, amount, yield_pct, is_special, ...}] (newest
first, capped at `count`) and an annual_totals list
[{year, amount, yield_pct}] suitable for a yearly bar chart.
All yields are emitted as percentages (4.5 = 4.5%), so plots don't
need to know which underlying field used decimal vs. percentage
encoding.
Use for: "AAPL dividend history", "yield trend over 5 years",
"dividend growth chart", "is the payout sustainable".
Args:
ticker: Stock ticker (e.g. 'AAPL', 'JNJ').
count: Number of most-recent individual payments to return
(default 16, max 100). The annual_totals series is
always returned in full.
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{'type': 'object', 'title': 'get_dividend_historyArguments', 'required': ['ticker'], 'properties': {'count': {'type': 'integer', 'title': 'Count', 'default': 16}, 'ticker': {'type': 'string', 'title': 'Ticker'}}}
get_earnings_calendar
Returns upcoming earnings dates across all stocks for a date range.
Args:
fromDate: Start date YYYY-MM-DD (default: today)
toDate: End date YYYY-MM-DD (default: 14 days from now)
exchange: Optional exchange filter, e.g. 'US' for US-only results
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{'type': 'object', 'title': 'get_earnings_calendarArguments', 'properties': {'toDate': {'type': 'string', 'title': 'Todate', 'default': ''}, 'exchange': {'type': 'string', 'title': 'Exchange', 'default': ''}, 'fromDate': {'type': 'string', 'title': 'Fromdate', 'default': ''}}}
get_earnings_call_summary
Returns the most recent earnings call summary for a ticker â
management guidance text, overall call sentiment (positive / neutral
/ negative with a one-line rationale), and AI-extracted highlights
and lowlights from the call as {title, content} bullets.
This is a structured summary derived from the call, not the raw
transcript text. Useful for "what did management say about X on the
last call", "was the most recent call bullish or bearish", or
"summarise the highlights from MSFT's latest earnings".
Only the most recent quarter is stored per ticker; for historical
EPS actual-vs-estimate series use get_earnings_history.
Args:
ticker: Stock ticker (e.g. 'AAPL', 'NVDA').
Returns:
{ ticker, fiscal_year, fiscal_quarter, guidance,
sentiment: { label, summary },
highlights: [ { title, content }, ... ],
lowlights: [ { title, content }, ... ] }
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{'type': 'object', 'title': 'get_earnings_call_summaryArguments', 'required': ['ticker'], 'properties': {'ticker': {'type': 'string', 'title': 'Ticker'}}}
get_earnings_history
Quarterly earnings time series for a ticker. Chart-ready: each
quarter row is {period, report_date, actual_eps, estimate_eps,
eps_surprise_pct, prior_year_eps, eps_yoy_change_pct, actual_revenue,
estimate_revenue, revenue_surprise_pct, net_income, ...}, ordered
oldest-first so a bar chart of actual vs. estimate EPS, or a YoY
trend line, plots directly.
Also returns next_quarter â the upcoming scheduled report with the
consensus estimate, low/high estimate band, and expected report date
â for forward-looking charts.
Use for: "AAPL earnings history", "earnings surprise trend", "did
NVDA beat last quarter", "EPS beat/miss the past 4 quarters".
Args:
ticker: Stock ticker (e.g. 'AAPL', 'NVDA').
quarters: Number of most-recent reported quarters to return
(default 8, max 40).
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{'type': 'object', 'title': 'get_earnings_historyArguments', 'required': ['ticker'], 'properties': {'ticker': {'type': 'string', 'title': 'Ticker'}, 'quarters': {'type': 'integer', 'title': 'Quarters', 'default': 8}}}
get_economic_calendar
Returns upcoming and recent economic events (Fed meetings, jobs reports, CPI, GDP).
Defaults to US events at High/Medium impact only because the raw feed includes
hundreds of low-impact items from every country.
Args:
daysBack: Days to look back (default 0)
daysForward: Days to look forward (default 7)
fromDate: Start date ISO format (alternative to daysBack)
toDate: End date ISO format (alternative to daysForward)
countries: Comma-separated country names to keep (default 'US').
Pass an empty string to disable the country filter.
Common values: 'US','UK','Germany','Japan','China','Canada','France'.
impact: Comma-separated impact levels to keep (default 'High,Medium').
Valid values: 'High','Medium','Low'. Pass empty to keep all levels.
limit: Max events returned after filtering (default 50, max 200).
Returns: { totalMatched, returned, filters, economicCalendar: [...] }.
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{'type': 'object', 'title': 'get_economic_calendarArguments', 'properties': {'limit': {'type': 'integer', 'title': 'Limit', 'default': 50}, 'impact': {'type': 'string', 'title': 'Impact', 'default': 'High,Medium', 'description': "Comma-separated impact levels to keep: High, Medium, Low (default 'High,Medium'); pass '' to keep all."}, 'toDate': {'type': 'string', 'title': 'Todate', 'default': ''}, 'daysBack': {'type': 'integer', 'title': 'Daysback', 'default': 0}, 'fromDate': {'type': 'string', 'title': 'Fromdate', 'default': ''}, 'countries': {'type': 'string', 'title': 'Countries', 'default': 'US', 'description': "Comma-separated country names to keep (default 'US'); pass '' to keep all. Examples: 'US','UK','Germany','Japan','China'."}, 'daysForward': {'type': 'integer', 'title': 'Daysforward', 'default': 7}}}
get_etf_analysis
Returns analyst consensus for ETFs based on weighted average of holdings' ratings.
Args:
tickers: Comma-separated ETF tickers (e.g. 'QQQ,SPY,VTI')
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{'type': 'object', 'title': 'get_etf_analysisArguments', 'required': ['tickers'], 'properties': {'tickers': {'anyOf': [{'type': 'string'}, {'type': 'array', 'items': {'type': 'string'}}], 'title': 'Tickers'}}}
get_etf_exposures
Returns the list of ETFs that hold a specific stock, sorted by holding market
value (largest first).
Args:
ticker: Stock ticker (e.g. 'MSFT', 'AAPL')
page: Page number (default 1)
page_size: Results per page (default 20, max 100)
Returns per ETF: etfTicker, etfCompanyName, etfCategory, aum, expenseRatio,
holdingWeight (% of ETF in this stock), holdingMarketValue ($),
holdingNumOfShares, weightInAsset (% of stock's outstanding shares held by this ETF),
etfAnalystConsensusScore, etfSmartScore. Also returns totalCount (total ETFs holding the stock).
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{'type': 'object', 'title': 'get_etf_exposuresArguments', 'required': ['ticker'], 'properties': {'page': {'type': 'integer', 'title': 'Page', 'default': 1}, 'ticker': {'type': 'string', 'title': 'Ticker'}, 'page_size': {'type': 'integer', 'title': 'Page Size', 'default': 20}}}
get_etf_forecast
Returns the analyst forecast for a specific ETF: consensus, price target, upside.
Args:
ticker: ETF ticker (e.g. 'QQQ')
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{'type': 'object', 'title': 'get_etf_forecastArguments', 'required': ['ticker'], 'properties': {'ticker': {'type': 'string', 'title': 'Ticker'}}}
get_etf_holdings
List the constituents of an ETF.
Base mode (default): returns every holding with its weight % in the
index â {ticker, name, weight_pct}.
Top-performers mode: pass `sort_by` (one of '5d', 'month', 'ytd',
'year') and a `limit` > 0 to get the top N constituents by that
period's return. Each row carries weight_pct, current_price,
return_pct for the chosen period, and analyst_consensus.
Use the top-performers mode for questions like 'which stocks in XLK
rose most this week' without separately calling a screener.
Args:
ticker: ETF ticker (e.g. 'SPY', 'QQQ').
sort_by: '' for full list, or one of '5d', 'month', 'ytd', 'year'.
limit: 0 to return all constituents; >0 (max 50) to return top N. A
negative or non-numeric limit is REJECTED rather than treated as 0 â
`limit` picks the mode here, so defaulting an unusable one would
answer a ranked top-N request with the full unranked list.
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{'type': 'object', 'title': 'get_etf_holdingsArguments', 'required': ['ticker'], 'properties': {'limit': {'type': 'integer', 'title': 'Limit', 'default': 0}, 'ticker': {'type': 'string', 'title': 'Ticker'}, 'sort_by': {'type': 'string', 'title': 'Sort By', 'default': '', 'description': "Optional prices field to sort by descending (e.g. 'prices.5d.gain', 'prices.twoWeeks.gain', 'prices.month.gain'); when set, returns top performers instead of the full list."}}}
get_etf_screener
Filters ETFs by asset class, category, and focus.
Args:
assetClass: Alternatives, AssetAllocation, Commodities, Currency, Equity, FixedIncome
category: BroadMarket, Sector, HighDividendYield, SizeAndStyle, Corporate, etc.
focus: LargeCap, SmallCap, MidCap, TotalMarket, Financials, HealthCare,
InformationTechnology, Energy, RealEstate, HighDividendYield, HighYield, etc.
Use this for a sector question ('tech ETFs' -> InformationTechnology);
the screener has no `sector` filter.
limit: Rows to return (default 20, max 100).
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{'type': 'object', 'title': 'get_etf_screenerArguments', 'properties': {'focus': {'type': 'string', 'title': 'Focus', 'default': '', 'description': "Focus filter, e.g. 'LargeCap', 'InformationTechnology', 'HighYield'. This is the screener's SECTOR filter â\x80\x94 there is no separate sector parameter."}, 'limit': {'type': 'integer', 'title': 'Limit', 'default': 0, 'description': 'Rows to return (default: 20, max: 100).'}, 'category': {'type': 'string', 'title': 'Category', 'default': '', 'description': "Category filter, e.g. 'Sector', 'BroadMarket', 'HighDividendYield'"}, 'assetClass': {'type': 'string', 'title': 'Assetclass', 'default': '', 'description': "Asset class filter, e.g. 'Equity', 'FixedIncome', 'Commodities'"}}}
get_etf_top_stocks
Returns the top stock holdings within an ETF along with their analyst ratings.
Args:
ticker: ETF ticker (e.g. 'QQQ')
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{'type': 'object', 'title': 'get_etf_top_stocksArguments', 'required': ['ticker'], 'properties': {'ticker': {'type': 'string', 'title': 'Ticker'}}}
get_financials
Financial statements time series for a ticker, chart-ready. Each
period is a flat ~25-field object spanning the income statement
(revenue, gross / operating / EBITDA / net margins, EPS, R&D),
the balance sheet (total assets, total debt, total equity, net
debt, cash + short-term investments), the cash flow statement
(operating cash flow, free cash flow, capex, dividends paid,
buybacks), and two computed ratios (current ratio, debt-to-equity).
Margins are emitted as percentages â gross_margin_pct of 49.27
means 49.27%. Cash outflows (dividends_paid, buybacks) are
returned as negative numbers, matching the source convention.
Use for: "AAPL revenue and FCF over the last 10 years", "show
margins trend", "is net debt rising", "EPS growth", "R&D as %
of revenue".
Args:
ticker: Stock ticker (e.g. 'AAPL', 'NVDA').
period: 'annual' (default), 'quarterly', or 'ttm' (trailing
twelve months). Annual periods extend ~9 years back;
quarterly extends ~37 quarters back.
count: Number of most-recent periods to return (default 5,
max 40), ordered oldest-first inside the returned
`periods` array.
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{'type': 'object', 'title': 'get_financialsArguments', 'required': ['ticker'], 'properties': {'count': {'type': 'integer', 'title': 'Count', 'default': 5}, 'period': {'type': 'string', 'title': 'Period', 'default': 'annual', 'description': "'annual' (default), 'quarterly', or 'ttm'"}, 'ticker': {'type': 'string', 'title': 'Ticker'}}}
get_forex_historical
Daily OHLC price history for a forex pair, covering the whole date range you ask for.
Chart-ready: while the range fits in one response, each row is the price feed's
own daily row â {symbol, date, open, high, low, close, volume, change,
changePercent, vwap} â newest first, ordered for direct plotting as an exchange-rate history.
A range too long to return day by day is aggregated into coarser OHLC bars
rather than cut short. `interval` names which (weekly/monthly/quarterly/yearly),
each bar spans `date` to `endDate`, and a bar's high/low are that period's real
extremes. Aggregated bars carry the same fields except `vwap`, which the feed
defines per session only. Re-request a narrower from_date/to_date for daily rows.
`summary` always describes the FULL requested window, computed from the daily
data: its first and last close with dates, its high and low with dates, and the
trailing changes the window reaches back far enough to support. Base any
"starting rate", "a year ago" or "period high/low" claim on `summary`, or on a
bar that is actually present.
`summary.windowHigh`/`windowLow` describe THIS window. A quote tool's
yearHigh/yearLow are the feed's trailing range, roughly the past 12-13
months â a different period â so label those as trailing-year figures. For the current level alone, call get_forex_quote.
`volume` on a forex row is a per-venue tick count, not market turnover â FX is
over-the-counter. Read it as a liquidity hint at best.
Args:
symbol: Forex pair symbol (e.g. 'EURUSD')
from_date: Start date YYYY-MM-DD (optional)
to_date: End date YYYY-MM-DD (optional)
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{'type': 'object', 'title': 'get_forex_historicalArguments', 'required': ['symbol'], 'properties': {'symbol': {'type': 'string', 'title': 'Symbol', 'description': "Forex pair, uppercase with no slash, e.g. 'EURUSD'."}, 'to_date': {'type': 'string', 'title': 'To Date', 'default': ''}, 'from_date': {'type': 'string', 'title': 'From Date', 'default': ''}}}
get_forex_quote
Returns the real-time exchange rate quote for a forex pair.
Common pairs: EURUSD, GBPUSD, USDJPY, USDCHF, AUDUSD, USDCAD.
yearHigh / yearLow are the feed's trailing-year range, roughly the past
12-13 months: call them trailing-year figures. For a year-to-date or
calendar-year change, a dated extreme or an exact 52-week figure use
get_forex_historical, since the quote does not date its extremes.
A pair quotes the BASE currency (first three letters) in units of the
QUOTE currency (last three): USDHUF 320 means 1 USD = 320 HUF. A rising
rate, or a rate above its priceAvg50 / priceAvg200, is the base
strengthening against the quote. changePercentage is measured against
previousClose as of the quote's timestamp. Spot FX is closed from Friday
17:00 to Sunday 17:00 New York time; a quote stamped in that window
shows the change as of the last close, not a move made that day.
Args:
symbol: Forex pair symbol (e.g. 'EURUSD')
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{'type': 'object', 'title': 'get_forex_quoteArguments', 'required': ['symbol'], 'properties': {'symbol': {'type': 'string', 'title': 'Symbol', 'description': "Forex pair, uppercase with no slash, e.g. 'EURUSD', 'GBPUSD', 'USDJPY'."}}}
get_hedge_fund_activity
Returns per-fund hedge-fund holdings and recent transactions for a ticker â
which institutions hold it, how much each changed (bought/sold), the holding
value, % of portfolio, and the fund's TipRanks rank/stars.
Complements get_hedge_fund_holdings (the aggregate share-count timeseries).
Args:
ticker: Stock ticker (e.g. 'AAPL')
limit: Max funds to return (default 25, max 100)
Returns JSON: {ticker, company, sentiment, trend_action, trend_value, funds}.
- funds: [{manager, institution, shares_change, direction, holding_value,
pct_of_portfolio, as_of, rank, stars, is_active}].
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{'type': 'object', 'title': 'get_hedge_fund_activityArguments', 'required': ['ticker'], 'properties': {'limit': {'type': 'integer', 'title': 'Limit', 'default': 25}, 'ticker': {'type': 'string', 'title': 'Ticker'}}}
get_hedge_fund_holdings
Hedge-fund share-count history for a ticker.
Returns the most recent `limit` snapshots (max 60) plus a summary
block (snapshot_count, first/last date and shares). Each row:
{date, shares}. Sourced from quarterly 13F filings; lags by up to
45 days.
For a snapshot of current sentiment without the timeseries, use
get_assets_data and read hedgeFundSentimentData.
Args:
ticker: Stock ticker (e.g. 'AAPL').
limit: Max snapshots to return (default 60, max 60).
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{'type': 'object', 'title': 'get_hedge_fund_holdingsArguments', 'required': ['ticker'], 'properties': {'limit': {'type': 'integer', 'title': 'Limit', 'default': 60}, 'ticker': {'type': 'string', 'title': 'Ticker'}}}
get_index_historical
Daily OHLC price history for a major market index, covering the whole date range you ask for.
Chart-ready: while the range fits in one response, each row is the price feed's
own daily row â {symbol, date, open, high, low, close, volume, change,
changePercent, vwap} â newest first, ordered for direct plotting as an index history.
A range too long to return day by day is aggregated into coarser OHLC bars
rather than cut short. `interval` names which (weekly/monthly/quarterly/yearly),
each bar spans `date` to `endDate`, and a bar's high/low are that period's real
extremes. Aggregated bars carry the same fields except `vwap`, which the feed
defines per session only. Re-request a narrower from_date/to_date for daily rows.
`summary` always describes the FULL requested window, computed from the daily
data: its first and last close with dates, its high and low with dates, and the
trailing changes the window reaches back far enough to support. Base any
"starting level", "a year ago" or "period high/low" claim on `summary`, or on a
bar that is actually present.
`summary.windowHigh`/`windowLow` describe THIS window. A quote tool's
yearHigh/yearLow are the feed's trailing range, roughly the past 12-13
months â a different period â so label those as trailing-year figures. For the current level alone, call get_index_quote.
Takes the same index symbols and broker/CFD-name mapping as
get_index_quote â e.g. ^NDX for 'US Tech 100' / 'Nasdaq 100', ^IXIC for
'Nasdaq Composite', ^GDAXI for 'Germany 40'.
Args:
symbol: Index symbol (e.g. '^GSPC' for S&P 500)
from_date: Start date YYYY-MM-DD
to_date: End date YYYY-MM-DD (defaults to today)
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{'type': 'object', 'title': 'get_index_historicalArguments', 'required': ['symbol', 'from_date'], 'properties': {'symbol': {'type': 'string', 'title': 'Symbol', 'description': "Index symbol, e.g. '^GSPC' for the S&P 500."}, 'to_date': {'type': 'string', 'title': 'To Date', 'default': ''}, 'from_date': {'type': 'string', 'title': 'From Date'}}}
get_index_quote
Returns the real-time quote for a major market index.
Index symbols: ^GSPC (S&P 500), ^NDX (Nasdaq 100), ^IXIC (Nasdaq
Composite), ^DJI (Dow Jones), ^RUT (Russell 2000), ^GSPTSE (TSX),
^FTSE (FTSE 100), ^GDAXI (DAX 40), ^FCHI (CAC 40), ^STOXX50E
(Euro STOXX 50), ^IBEX (IBEX 35), ^N225 (Nikkei), ^AXJO (ASX 200),
^AORD (All Ords), ^HSI (Hang Seng), ^STI (STI), ^BSESN (Sensex),
^VIX (VIX).
Broker / CFD names map to the index they track (the same map the AI
chat uses): 'US Tech 100' / 'NAS100' / 'USTEC' -> ^NDX; 'US 500' /
'SPX500' -> ^GSPC; 'Wall Street 30' / 'US 30' -> ^DJI; 'US 2000' /
'US Small Cap 2000' -> ^RUT; 'Germany 40' / 'GER40' -> ^GDAXI;
'UK 100' -> ^FTSE; 'France 40' -> ^FCHI; 'Euro 50' / 'EU50' ->
^STOXX50E; 'Spain 35' -> ^IBEX; 'Japan 225' -> ^N225; 'Australia 200'
-> ^AXJO; 'Hong Kong 50' -> ^HSI. 'Nasdaq Composite' is
^IXIC; 'Nasdaq 100' and the Nasdaq 100 CFD names above are ^NDX â
different indices at different levels, so quote the one the user named
and name it. A bare 'Nasdaq' is ambiguous: say which one you quote. For
an index not listed here (e.g. 'S&P 100'), call it by its own symbol â
a listed index with a similar name is a different index.
yearHigh / yearLow are the feed's trailing-year range, roughly the past
12-13 months: call them trailing-year figures. For a year-to-date or
calendar-year change, a dated extreme or an exact 52-week figure use
get_index_historical, since the quote does not date its extremes.
Args:
symbol: Index symbol (e.g. '^GSPC' for S&P 500)
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{'type': 'object', 'title': 'get_index_quoteArguments', 'required': ['symbol'], 'properties': {'symbol': {'type': 'string', 'title': 'Symbol', 'description': "Index symbol, e.g. '^GSPC' for the S&P 500."}}}
get_insider_transactions
Individual corporate-insider (officers/directors, Form 4) transactions for
a ticker, newest first.
Each row: insider_name, role, is_officer, is_director, action (e.g.
"Auto Sell", "Grant/Award/Other Acquisition"), side (buy/sell), shares,
price (approximate â value / shares; the source has no exact price), value,
date, filing_link (the SEC Form-4 URL), and insider_stars.
This is corporate-insider activity (Form 4). For retail/individual
investor sentiment, use get_assets_data and read investorActivity.
Args:
ticker: Stock ticker (e.g. 'AAPL').
limit: Max rows to return (default 30, max 100).
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{'type': 'object', 'title': 'get_insider_transactionsArguments', 'required': ['ticker'], 'properties': {'limit': {'type': 'integer', 'title': 'Limit', 'default': 30}, 'ticker': {'type': 'string', 'title': 'Ticker'}}}
get_investor_sentiment
Returns crowd / retail investor sentiment for a stock.
Args:
ticker: Stock ticker (e.g. 'NVDA')
Returns JSON with these top-level keys:
- investorStatsOverview: stats aggregated across ALL TipRanks
portfolios that hold the ticker. Fields:
* numberOfPortfolios: total active portfolios on the platform.
* portfoliosHoldingStock: how many of them hold THIS ticker.
* averageAllocation: average % allocation among holders (decimal).
* percentOverLast30Days / percentOverLast7Days: change in the
count of holders over the window (decimal; 0.013 = +1.3%).
* investorScore: TipRanks' 0-1 score of how confident "the
crowd" is on this stock; higher = more bullish positioning.
* sectorAverageScore: investorScore averaged across the sector,
for comparison.
* sentiment: bucketed label â one of "VeryNegative",
"Negative", "Neutral", "Positive", "VeryPositive".
* sectorAverageSentiment: same bucket, sector-wide.
- bestInvestorStatsOverview: same fields, but restricted to "Best
Investors" â TipRanks users with top-decile portfolio returns
over the trailing window. If investorStatsOverview and
bestInvestorStatsOverview diverge (e.g. crowd is Positive but
best investors are Negative), that's the headline signal.
- ageDistribution: holders split by TipRanks account-tenure tier
(NOT the investor's biological age):
* eldest: oldest accounts on the platform
* midRange: middle tier
* youngest: newest accounts
Each has percentHolders, last30DaysChange, last7DaysChange,
and per-bucket averages (averageBeta, averageMonthlyReturn,
dividendYield, averagePeRatio).
- investorsAlsoBought: top other stocks held by people who hold
this one (each: ticker, companyName, averageHoldingSize,
lastSevenDayChange, lastThirtyDayChange, sector, sectorName,
score, sentiment, marketCap, marketCapCurrencyCode).
- investorsAlsoBoughtYoungest / MidRange / Eldest: same shape,
filtered to that account-tenure bucket. Often shorter or
empty for stocks held mostly by one cohort.
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{'type': 'object', 'title': 'get_investor_sentimentArguments', 'required': ['ticker'], 'properties': {'ticker': {'type': 'string', 'title': 'Ticker'}}}
get_ipo_calendar
Returns upcoming and recent IPOs.
Args:
fromDate: Start date ISO format (default: today)
toDate: End date ISO format (default: 30 days from now)
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{'type': 'object', 'title': 'get_ipo_calendarArguments', 'properties': {'toDate': {'type': 'string', 'title': 'Todate', 'default': ''}, 'fromDate': {'type': 'string', 'title': 'Fromdate', 'default': ''}}}
get_latest_news
Latest TipRanks news articles (newest first) from TipRanks's own
editorial/wire feed â each with a text excerpt, unlike get_assets_news.
Use for general market news (no ticker), news on a specific stock with a
short summary of each story, or to browse a news category. This is also the
tool for news from a specific PAST date range â pass from_date AND to_date
together; the archive holds years of stories, so a past window is answerable
here even though get_assets_news only reaches recent articles.
Args:
tickers: Optional comma-separated tickers to filter by (e.g. 'NVDA,AAPL').
Omit for general market news.
category: Optional single category (see the field description).
from_date: Optional 'YYYY-MM-DD' recency floor.
limit: Max articles to return (default 20).
to_date: Optional 'YYYY-MM-DD' inclusive upper bound. Results are
newest-first, so from_date alone returns today's news rather
than news from around that date â add to_date to scope a window.
Returns a JSON list of {id, title, excerpt, author, category, date, url,
tickers}. To read a full article, pass its url or id to get_article.
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{'type': 'object', 'title': 'get_latest_newsArguments', 'properties': {'limit': {'type': 'integer', 'title': 'Limit', 'default': 20}, 'tickers': {'anyOf': [{'type': 'string'}, {'type': 'array', 'items': {'type': 'string'}}], 'title': 'Tickers', 'default': ''}, 'to_date': {'type': 'string', 'title': 'To Date', 'default': '', 'description': "Optional 'YYYY-MM-DD' upper bound on the publish date, inclusive of that whole day. Pair with from_date to read a specific past window; from_date on its own returns the newest stories since that date."}, 'category': {'type': 'string', 'title': 'Category', 'default': '', 'description': "Optional single category: 'news', 'the-fly', 'blurbs', 'catalyst', 'ratings', 'cryptocurrencies', 'insider-trading', 'newswire', 'private-companies', 'company-announcements'. Omitted = editorial/wire feed (excludes auto-ingested company-announcements)."}, 'from_date': {'type': 'string', 'title': 'From Date', 'default': ''}}}
get_market_commentary
Cached equities market sentiment snapshot.
Returns {overallSentiment, atmosphere, keyThemes, tailwinds, headwinds}.
Generated by TipRanks' AI pipeline with web search, refreshed every
~4 hours; this endpoint reads the cache only and does not trigger
regeneration. If no recent cache exists, returns
{"status": "unavailable"}.
The content is AI-generated commentary, not authoritative TipRanks
market data â present it as such to end users.
只读
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幂等
输入模式
{'type': 'object', 'title': 'get_market_commentaryArguments', 'properties': {}}
get_market_movers
Returns today's market movers: biggest gainers, losers, most active.
Args:
category: 1=DollarVolume, 2=PercentGainers, 3=PercentLosers,
4=GainersRegular, 5=LosersRegular, 6=UnusualVolume
country: 1=US, 2=Canada, 3=UK
num: Number of results
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幂等
输入模式
{'type': 'object', 'title': 'get_market_moversArguments', 'required': ['category'], 'properties': {'num': {'type': 'integer', 'title': 'Num', 'default': 20}, 'country': {'type': 'integer', 'title': 'Country', 'default': 1, 'description': '1=US, 2=Canada, 3=UK (default: 1)'}, 'category': {'type': 'integer', 'title': 'Category', 'description': '1=DollarVolume, 2=PercentGainers (ext hours), 3=PercentLosers (ext hours), 4=GainersRegular, 5=LosersRegular, 6=UnusualVolume'}}}
get_market_performance
Returns market-wide performance for a specific country: average returns,
sector breakdown, top/bottom performers.
Args:
country: Country code: 'us', 'ca', 'gb', 'de', 'il', 'au', 'hk', 'sg', etc.
只读
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幂等
输入模式
{'type': 'object', 'title': 'get_market_performanceArguments', 'properties': {'country': {'type': 'string', 'title': 'Country', 'default': 'us'}}}
get_my_usage
Your current TipRanks MCP usage against the monthly tool-call quota.
Reports calls used this calendar month, your limit, how many remain, your
plan tier, and when the quota resets (UTC). Handy to check before running a
large batch of calls. This call is free â it never counts against the quota.
What counts: every tool call is metered once whether or not it returns data,
so an unrecognised ticker or an invalid argument costs the same as a
successful call. The connection handshake (initialize, tools/list and the
other discovery calls) is never metered, and neither is this tool.
Calls refused for being over the limit are refunded on both ladders, so
`used` settles at the cap rather than climbing while a client retries. It
can still read higher than `limit` when the ceiling FELL mid-month â a
complimentary grant expiring or being revoked, or a paid MCP subscription
lapsing â and there it is the count of calls genuinely served before the
cap dropped.
只读
可访问外部资源
幂等
输入模式
{'type': 'object', 'title': 'get_my_usageArguments', 'properties': {}}
get_options_chain
Contracts at one expiration, enriched with price + OI + volume.
Each row: ticker (OCC), contract_type, strike, name, price, volume,
open_interest, open_interest_change, change_percent, day_open / high /
low, last_trade_date.
Quotes are typically delayed ~15 minutes. Greeks and implied
volatility are NOT exposed by this data source â do not fabricate
them.
Args:
ticker: Underlying (e.g. 'AAPL').
expiration_date: One of the dates from get_options_expirations
(YYYY-MM-DD).
contract_type: '' for both, or 'call' or 'put'.
strike_gte: Filter strikes >= this value (optional).
strike_lte: Filter strikes <= this value (optional).
limit: Max contracts to return (default 50).
只读
可访问外部资源
幂等
输入模式
{'type': 'object', 'title': 'get_options_chainArguments', 'required': ['ticker', 'expiration_date'], 'properties': {'limit': {'type': 'integer', 'title': 'Limit', 'default': 50}, 'ticker': {'type': 'string', 'title': 'Ticker'}, 'strike_gte': {'anyOf': [{'type': 'number'}, {'type': 'null'}], 'title': 'Strike Gte', 'default': None}, 'strike_lte': {'anyOf': [{'type': 'number'}, {'type': 'null'}], 'title': 'Strike Lte', 'default': None}, 'contract_type': {'type': 'string', 'title': 'Contract Type', 'default': '', 'description': "'call' or 'put'; omit to return both sides."}, 'expiration_date': {'type': 'string', 'title': 'Expiration Date', 'description': 'Exact expiration in YYYY-MM-DD. REQUIRED â\x80\x94 call get_options_expirations first to discover valid dates.'}}}
get_options_contract
Snapshot one OCC contract â price, OI, intraday OHLCV, last trade.
The contract_ticker is an OCC-format symbol like 'O:AAPL260520C00205000'
(O: + underlying + YYMMDD + C/P + strike-in-thousandths-8-digits).
The 'O:' prefix is optional.
Quotes are typically delayed ~15 minutes. Greeks and implied
volatility are not available from this data source.
Args:
contract_ticker: OCC contract symbol.
只读
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幂等
输入模式
{'type': 'object', 'title': 'get_options_contractArguments', 'required': ['contract_ticker'], 'properties': {'contract_ticker': {'type': 'string', 'title': 'Contract Ticker', 'description': "OCC-format option ticker, e.g. 'O:AAPL260520C00205000'. The 'O:' prefix is optional."}}}
get_options_expirations
List future expiration dates for a ticker's listed options.
Excludes past expirations. Use the result as input to get_options_chain.
Args:
ticker: Underlying ticker (e.g. 'AAPL').
只读
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幂等
输入模式
{'type': 'object', 'title': 'get_options_expirationsArguments', 'required': ['ticker'], 'properties': {'ticker': {'type': 'string', 'title': 'Ticker'}}}
get_options_unusual_trades
Recent unusual option trades for an underlying (size/sweep alerts).
Returns the most recent `limit` flagged trades with the side, strike,
expiry, size, and notional value. Useful for spotting large bullish
or bearish positioning.
Args:
ticker: Underlying ticker (e.g. 'AAPL').
limit: Max trades to return (default 25).
只读
可访问外部资源
幂等
输入模式
{'type': 'object', 'title': 'get_options_unusual_tradesArguments', 'required': ['ticker'], 'properties': {'limit': {'type': 'integer', 'title': 'Limit', 'default': 25}, 'ticker': {'type': 'string', 'title': 'Ticker'}}}
get_peers
Peer/competitor companies for a stock, with comparative metrics for
side-by-side analysis. Read-only, no side effects.
Use to find and compare a company against similar names (competitors,
same-sector peers). For that company's own data use get_assets_data; for a
sector-wide breakdown use get_sector_analysis.
只读
可访问外部资源
幂等
输入模式
{'type': 'object', 'title': 'get_peersArguments', 'required': ['ticker'], 'properties': {'ticker': {'type': 'string', 'title': 'Ticker', 'description': "Stock ticker symbol, e.g. 'AAPL'."}}}
get_politician_activity
Returns a specific politician's stock trades or holdings.
First call get_politicians to find the politicianId.
Args:
politicianId: Politician ID from get_politicians
activity: 'trades' or 'holdings'
只读
可访问外部资源
幂等
输入模式
{'type': 'object', 'title': 'get_politician_activityArguments', 'required': ['politicianId'], 'properties': {'activity': {'type': 'string', 'title': 'Activity', 'default': 'trades', 'description': "'trades' or 'holdings' (default: trades)"}, 'politicianId': {'type': 'integer', 'title': 'Politicianid', 'description': 'Politician ID, as returned by get_politicians.'}}}
get_politicians
Returns the list of politicians tracked for trading activity.
Returns: name, party, state, position, net worth, profile.
只读
可访问外部资源
幂等
输入模式
{'type': 'object', 'title': 'get_politiciansArguments', 'properties': {}}
get_portfolio_analysis
Returns asset allocation by type/country/top stocks and distribution by sector,
market cap, dividend yield, beta, and P/E.
Args:
portfolio_id: One of the IDs returned by list_my_portfolios.
只读
可访问外部资源
幂等
输入模式
{'type': 'object', 'title': 'get_portfolio_analysisArguments', 'required': ['portfolio_id'], 'properties': {'portfolio_id': {'type': 'integer', 'title': 'Portfolio Id'}}}
get_portfolio_holdings
Returns all holdings for one of your TipRanks portfolios.
Per holding: ticker, shares, price, cost basis (AvgExecutionPrice),
P/E ratio, dividend yield, market cap, sector, country, 52-week high/low,
percentage of portfolio, beta, EPS. Plus total value, cash, stock count.
Args:
portfolio_id: One of the IDs returned by list_my_portfolios.
只读
可访问外部资源
幂等
输入模式
{'type': 'object', 'title': 'get_portfolio_holdingsArguments', 'required': ['portfolio_id'], 'properties': {'portfolio_id': {'type': 'integer', 'title': 'Portfolio Id'}}}
get_portfolio_overview
Returns lifetime / 1mo / 6mo / 12mo / YTD returns, Sharpe ratio, and a
monthly-return time series. The monthly history field is chart-ready â
a list of {month, return} points suitable for direct plotting.
Args:
portfolio_id: One of the IDs returned by list_my_portfolios.
只读
可访问外部资源
幂等
输入模式
{'type': 'object', 'title': 'get_portfolio_overviewArguments', 'required': ['portfolio_id'], 'properties': {'portfolio_id': {'type': 'integer', 'title': 'Portfolio Id'}}}
get_portfolio_performance
Returns full performance: stats, gains, best trade, recent activity, a
daily-yield time series benchmarked against S&P 500 (chart-ready â
aligned dates with portfolio and benchmark yield columns, plot directly
as overlaid lines), monthly returns, risk profile, beta, dividend
yield/amount.
Args:
portfolio_id: One of the IDs returned by list_my_portfolios.
只读
可访问外部资源
幂等
输入模式
{'type': 'object', 'title': 'get_portfolio_performanceArguments', 'required': ['portfolio_id'], 'properties': {'portfolio_id': {'type': 'integer', 'title': 'Portfolio Id'}}}
get_recent_analyst_ratings
Recent Wall Street analyst rating actions on a single stock, covering the
trailing 12 months (newest first).
Each row carries the analyst's name and firm, the rating (Buy/Hold/Sell),
the action (initiated/upgraded/downgraded/reiterated/maintained), the price
target, and the analyst's TipRanks credibility (numOfStars 0-5, rank,
success rate, average return) plus the source article title/quote.
For the aggregate consensus and average/best price target, use
get_assets_data instead.
Args:
ticker: Stock ticker (e.g. 'NVDA', 'AAPL').
Returns: a list of rating actions. recommendationDate is a 'MM/DD/YYYY'
string; numOfStars is the analyst's 0-5 TipRanks star rating.
只读
可访问外部资源
幂等
输入模式
{'type': 'object', 'title': 'get_recent_analyst_ratingsArguments', 'required': ['ticker'], 'properties': {'ticker': {'type': 'string', 'title': 'Ticker'}}}
get_sector_analysis
Returns sector-level analysis for all 11 US sectors: average P/E, analyst
upside, buy ratio, stock count. Sorted by average analyst upside.
只读
可访问外部资源
幂等
输入模式
{'type': 'object', 'title': 'get_sector_analysisArguments', 'properties': {}}
get_stock_catalyst
TipRanks-generated catalyst summary explaining why a stock is moving.
Each entry: {ticker, summary, sentiment, updated} where sentiment is
'positive' | 'neutral' | 'negative'. Updated throughout the trading
day. Use to explain today's move for a specific stock.
Args:
tickers: Comma-separated tickers (e.g. 'AMZN' or 'AMZN,NVDA').
只读
可访问外部资源
幂等
输入模式
{'type': 'object', 'title': 'get_stock_catalystArguments', 'required': ['tickers'], 'properties': {'tickers': {'anyOf': [{'type': 'string'}, {'type': 'array', 'items': {'type': 'string'}}], 'title': 'Tickers'}}}
get_stock_prices
Historical daily closing prices for up to 5 stocks or ETFs.
Per ticker: {ticker, period, series:[{date, price}], summary} with
summary fields first_price, last_price, change_pct, high, low,
trading_days. Series is downsampled to ~250 evenly-spaced points
(latest point always retained) so the payload stays small for charting.
`period` must be one of: 1m, 3m, 6m, ytd, 1y, 2y, 3y, 5y, all.
Args:
tickers: Comma-separated tickers, up to 5 (e.g. 'AAPL,MSFT').
period: Lookback window (default 'ytd').
只读
可访问外部资源
幂等
输入模式
{'type': 'object', 'title': 'get_stock_pricesArguments', 'required': ['tickers'], 'properties': {'period': {'type': 'string', 'title': 'Period', 'default': 'ytd'}, 'tickers': {'anyOf': [{'type': 'string'}, {'type': 'array', 'items': {'type': 'string'}}], 'title': 'Tickers'}}}
get_stock_quotes
Real-time price quote for one or more stocks or ETFs.
Returns price, intraday OHLC, day change (amount + percent), volume,
previous close, market cap, currency, exchange, and market-state
flags (is_market_open / is_premarket / is_after_market). When
extended-hours data is present, the entry includes a
`pre_post_market` block â when the regular session is closed,
that's the freshest price.
For forex pairs use get_forex_quote; this endpoint is stocks/ETFs only.
Args:
tickers: Comma-separated tickers (e.g. 'AAPL' or 'AAPL,MSFT,NVDA').
只读
可访问外部资源
幂等
输入模式
{'type': 'object', 'title': 'get_stock_quotesArguments', 'required': ['tickers'], 'properties': {'tickers': {'anyOf': [{'type': 'string'}, {'type': 'array', 'items': {'type': 'string'}}], 'title': 'Tickers'}}}
get_stock_splits
Returns the stock-split calendar with split ratios and direction
(Forward / Reverse). Use for upcoming splits, reverse-split alerts,
historical split lookup.
Args:
fromDate: Start date YYYY-MM-DD (default: 30 days ago)
toDate: End date YYYY-MM-DD (default: 30 days from now)
type: Optional filter â 'Forward' or 'Reverse' (case-insensitive).
Empty string returns both.
limit: Max rows (default: 25, max: 100)
ticker: Optional single symbol. Widen fromDate to search a company's history â
the default window is only today ± 30 days.
Returns: { totalCount, data: [{ ticker, companyName, effectiveDate, type,
splitRatio, splitRatioText }] }. A filtered call
(ticker or type) also returns `matched` and `window`: `totalCount` is
every split in the window, `matched` how many passed the filter. The
window is read in full before filtering, so an empty result means there
genuinely are none rather than that the first page held none.
只读
可访问外部资源
幂等
输入模式
{'type': 'object', 'title': 'get_stock_splitsArguments', 'properties': {'type': {'type': 'string', 'title': 'Type', 'default': '', 'description': "Optional filter: 'Forward' or 'Reverse' (case-insensitive); omit to return both."}, 'limit': {'type': 'integer', 'title': 'Limit', 'default': 25}, 'ticker': {'type': 'string', 'title': 'Ticker', 'default': '', 'description': "Optional. Return only this company's splits within the window, e.g. 'NVDA'. Pair with a wide fromDate for 'has X ever split'."}, 'toDate': {'type': 'string', 'title': 'Todate', 'default': ''}, 'fromDate': {'type': 'string', 'title': 'Fromdate', 'default': ''}}}
get_technical_analysis
Returns RSI, MACD, Stochastics, ADX, moving averages, and pivot points
for stocks and ETFs.
Covers stocks and ETFs alike (e.g. 'NVDA', 'SPY', 'QQQ', 'VTI') with the
same payload shape. For an ETF's analyst consensus, forecast, holdings or
exposures, use get_etf_analysis, get_etf_forecast, get_etf_top_stocks, or
get_etf_exposures.
Args:
tickers: Comma-separated stock or ETF tickers (e.g. 'NVDA' or 'NVDA,SPY').
timeFrame: '1m','5m','15m','30m','1h','5h','day','3d','week','2w','month' (default: 'day')
'5h' is slow upstream: request it for one ticker per call.
Returns: summary scores, oscillators (RSI, MACD, Stochastics, ADX, CCI,
Williams %R, ATR, ROC), moving averages, and pivot points.
Labels are strings. indicator: "Buy", "Neutral" or "Sell" (null
on ATR and pivot points). scoreScale: "StrongBuy", "Buy",
"Neutral", "Sell" or "StongSell" (the upstream's own spelling).
只读
可访问外部资源
幂等
输入模式
{'type': 'object', 'title': 'get_technical_analysisArguments', 'required': ['tickers'], 'properties': {'tickers': {'anyOf': [{'type': 'string'}, {'type': 'array', 'items': {'type': 'string'}}], 'title': 'Tickers'}, 'timeFrame': {'type': 'string', 'title': 'Timeframe', 'default': 'day', 'description': "One of '1m','5m','15m','30m','1h','5h','day','3d','week','2w','month' (default: 'day'). Request '5h' for one ticker per call."}}}
get_ticker_earnings
Upcoming and recent earnings dates for a specific stock â scheduled
report dates with EPS/revenue estimates where available. Read-only, no
side effects.
Use this to find when a company reports. For past actual-vs-estimate
results use get_earnings_history; for a cross-market schedule use
get_earnings_calendar.
只读
可访问外部资源
幂等
输入模式
{'type': 'object', 'title': 'get_ticker_earningsArguments', 'required': ['ticker'], 'properties': {'ticker': {'type': 'string', 'title': 'Ticker', 'description': "Stock ticker symbol, e.g. 'NVDA'."}}}
get_top_hedge_fund_managers
Returns top-performing hedge fund managers ranked by success rate and returns.
Args:
num: Number of managers to return (default 10, max 100 â the upstream
returns 100 for anything higher)
只读
可访问外部资源
幂等
输入模式
{'type': 'object', 'title': 'get_top_hedge_fund_managersArguments', 'properties': {'num': {'type': 'integer', 'title': 'Num', 'default': 10}}}
get_top_rated_stocks
Returns stocks most recommended by the best-performing analysts (by analyst track record).
Args:
num: Number of results
sector: Sector filter (financial, healthcare, technology, etc.) or empty for all
country: 'US', 'Canada', 'UK', 'Global'. NOTE: UK tickers use GB: prefix but country param is 'UK'.
只读
可访问外部资源
幂等
输入模式
{'type': 'object', 'title': 'get_top_rated_stocksArguments', 'properties': {'num': {'type': 'integer', 'title': 'Num', 'default': 20}, 'sector': {'type': 'string', 'title': 'Sector', 'default': '', 'description': 'Lowercase sector filter: financial, healthcare, consumerdefensive, consumercyclical, utilities, materials, technology, industrials, energy, communicationservices, realestate (default: all sectors)'}, 'country': {'type': 'string', 'title': 'Country', 'default': 'US', 'description': "'US', 'Canada', 'UK', or 'Global' (default: US). UK tickers are returned with a 'GB:' prefix but the country value is still 'UK'."}}}
get_top_smart_score_stocks
Returns stocks with the highest TipRanks Smart Score (perfect 10 / Outperform).
Args:
num: Number of results
sector: Sector filter (financial, healthcare, technology, etc.) or empty for all
country: 'US', 'Canada', 'UK', 'Germany', 'Spain', 'France', 'India', 'Italy',
'Israel', 'Australia', 'Singapore', 'Japan', 'HongKong', 'Global'.
NOTE: UK tickers use GB: prefix but the country param is 'UK'.
只读
可访问外部资源
幂等
输入模式
{'type': 'object', 'title': 'get_top_smart_score_stocksArguments', 'properties': {'num': {'type': 'integer', 'title': 'Num', 'default': 20}, 'sector': {'type': 'string', 'title': 'Sector', 'default': '', 'description': 'Lowercase sector filter: financial, healthcare, consumerdefensive, consumercyclical, utilities, materials, technology, industrials, energy, communicationservices, realestate (default: all sectors)'}, 'country': {'type': 'string', 'title': 'Country', 'default': 'US', 'description': "'US','Canada','UK','Germany','Spain','France','India','Italy','Israel','Australia','Singapore','Japan','HongKong', or 'Global' (default: US). UK tickers are returned with a 'GB:' prefix but the country value is still 'UK'."}}}
get_trending_stocks
Returns currently trending stocks that recently received analyst ratings.
Args:
num: Number of results (default 20)
filter: exactly one of 'analysts', 'bloggers', 'both'. Anything else is
refused â the feed would otherwise answer it with the 'both' list.
daysAgo: Days to look back: 3, 7, or any number from 30 up. Every other value
(1, 2, 14â¦) is rejected by the feed. Default 7. Pass 30 or more when
filtering by sector or country to ensure enough results â narrow
windows often return fewer than 5 stocks in a specific sector.
trendingType: exactly 'best-rated' or 'worst-rated' (empty for all). Anything
else is refused â the feed would otherwise return the unranked list.
country: 'US','Canada','UK','Germany','Israel','Australia' etc.
sector: One of energy, financial, general, healthcare, industrials, services,
technology, utilities. Empty for all sectors. This feed answers a
sector it does not recognise with financial stocks rather than an
error, so anything outside that list comes back refused instead.
Rows returned for 'energy' are energy companies (Exxon, Chevron, BP)
even though the feed tags them UTILITIES.
Returns: ticker, SmartScore, analyst/blogger sentiment, hedge fund trend,
price target, buy/hold/sell counts per stock.
只读
可访问外部资源
幂等
输入模式
{'type': 'object', 'title': 'get_trending_stocksArguments', 'properties': {'num': {'type': 'integer', 'title': 'Num', 'default': 20}, 'filter': {'type': 'string', 'title': 'Filter', 'default': 'analysts', 'description': "Exactly one of 'analysts', 'bloggers' or 'both' (default: analysts). Any other value is rejected rather than answered."}, 'sector': {'type': 'string', 'title': 'Sector', 'default': '', 'description': "Sector filter: energy, financial, general, healthcare, industrials, services, technology or utilities. Omit for all sectors; a sector outside this list is refused rather than answered. Rows for sector='energy' are energy companies even though the feed labels them UTILITIES."}, 'country': {'type': 'string', 'title': 'Country', 'default': 'US', 'description': "Country name, e.g. 'US','Canada','UK','Germany','Israel','Australia' (default: US)"}, 'daysAgo': {'type': 'integer', 'title': 'Daysago', 'default': 7, 'description': 'Days to look back: 3, 7, or any number from 30 up â\x80\x94 anything else (1, 2, 14â\x80¦) is rejected. Default 7. Use 30 or more when filtering by sector or country, as narrow windows often return very few stocks.'}, 'trendingType': {'type': 'string', 'title': 'Trendingtype', 'default': '', 'description': "Exactly 'best-rated' or 'worst-rated'; omit for all (default). Any other value is rejected rather than silently returning the unranked list."}}}
list_my_portfolios
List the portfolios you authorized this connector to access.
Returns the portfolios that were on your TipRanks account at the time
you signed in, each with its id and name. If you've added or renamed
portfolios since, re-authorize to refresh.
只读
可访问外部资源
幂等
输入模式
{'type': 'object', 'title': 'list_my_portfoliosArguments', 'properties': {}}
历史
近期工具变更
已更改
get_ai_stock_analysis
2026年9月29日 03:03
已更改
get_crypto_historical
2026年9月29日 03:03
已更改
get_crypto_quote
2026年9月29日 03:03
已更改
get_index_historical
2026年9月29日 03:03
已更改
get_index_quote
2026年9月29日 03:03
已更改
get_forex_historical
2026年9月29日 03:03
已更改
get_forex_quote
2026年9月29日 03:03
已更改
get_commodity_historical
2026年9月29日 03:03
已更改
get_commodity_quote
2026年9月29日 03:03
已更改
get_technical_analysis
2026年9月29日 03:03
已更改
get_latest_news
2026年9月29日 03:03
已添加
get_my_usage
2026年9月17日 12:38
已添加
get_options_unusual_trades
2026年9月17日 12:38
已添加
get_options_contract
2026年9月17日 12:38
已添加
get_options_chain
2026年9月17日 12:38
已添加
get_options_expirations
2026年9月17日 12:38
已添加
get_recent_analyst_ratings
2026年9月17日 12:38
已添加
get_analysts_by_firm
2026年9月17日 12:38
已添加
get_etf_holdings
2026年9月17日 12:38
已添加
get_hedge_fund_holdings
2026年9月17日 12:38
已添加
get_insider_transactions
2026年9月17日 12:38
已添加
get_market_commentary
2026年9月17日 12:38
已添加
get_stock_catalyst
2026年9月17日 12:38
已添加
get_stock_prices
2026年9月17日 12:38
已添加
get_stock_quotes
2026年9月17日 12:38
已添加
get_dividend_history
2026年9月17日 12:38
已添加
get_ai_stock_analysis
2026年9月17日 12:38
已添加
get_earnings_call_summary
2026年9月17日 12:38
已添加
get_financials
2026年9月17日 12:38
已添加
get_earnings_history
2026年9月17日 12:38
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World Monitor
app.worldmonitor/mcp
Delivers live geopolitical, conflict, country-risk, market, energy, climate, aviation, supply-chain, and macroeconomic intelligen…
Slacking.biz — SEC Financial Data + US Economics + Demographics + FX
io.github.Th3Slack3r/slacking-biz
Provides financial, economic, demographic, foreign-exchange, regulatory, and company research data from public sources.
welcome
com.thebalancedinvestorclub/welcome
Provides market data and educational investment research for stocks, ETFs, and crypto, including fundamentals, prices, macro indi…
Currencyformat
io.github.pipeworx-io/currencyformat
Formats localized numbers and currencies and also provides routed access to structured financial, market, government, and researc…
Unpaywall
io.github.pipeworx-io/unpaywall
Provides open-access scholarly paper lookup plus routed research and structured data queries across financial, economic, scientif…