MCP 서버

quantifyme

            ai.quantifyme/quantifyme
        

금융 및 투자 공개 · 연결 가능 MCP 2025-11-25

이 MCP로 할 수 있는 일

Converts plain-language trading strategies into deployable live signal models.

browse_community

Browse Community Strategies (leaderboard)

Browse the public community leaderboard of published strategies, ranked by a composite performance score (best first). No signup or key needed. Copy-trade flow: call this to find a top strategy, then pass its `id` to `one_shot` as `community_id` to deploy a live signal model running that exact strategy in one call. Args: limit: How many top entries to return (default 20, max 200). sort: Ranking metric, best-first â one of "composite" (default), "ret" (total return), "wr" (win rate), "sharpe", "n_trades". Mirrors the quantifyme.ai/community page's sortable columns, so an agent can pick the top strategy by the metric it cares about in one call. The sorted entries keep their `id`, so the winner is directly deployable via one_shot(community_id=...). Returns: dict with: - scripts (list[dict]): ranked entries, best first. Each has: id (int â pass to one_shot as community_id), username, title, description, created_at, score, and metrics {total_ret, sharpe_strat, win_rate, n_trades, mdd, profit_factor}. SHOW the top few with their win_rate / total_ret so the user can pick one. - count (int). - metric (str): the sort key applied.

읽기 전용 외부 접근 가능 멱등성

입력 스키마

{'type': 'object', 'title': 'browse_communityArguments', 'properties': {'sort': {'type': 'string', 'title': 'Sort', 'default': 'composite'}, 'limit': {'type': 'integer', 'title': 'Limit', 'default': 20}}}

출력 스키마

{'type': 'object', 'title': 'browse_communityDictOutput', 'additionalProperties': True}

find_strategy

Find a Matching Strategy

Find an existing PROVEN strategy that matches a plain-English idea, so you can offer the user a choice â deploy the existing one, or generate a fresh custom one. Mirrors the quantifyme.ai landing experience: "Found <X> by @<author> (WR/PF) â Use it / Generate fresh". CALL THIS FIRST when a user describes a strategy idea. Then present the match (if any) and ASK which they want: â¢ Use it â one_shot(community_id=<match.community_id>) â deploys the exact proven strategy (free, no generation). â¢ Generate fresh â one_shot(prompt="<their description>") â Claude writes a brand-new custom strategy for them. If there's no match, just offer to generate fresh. Args: description: the user's strategy idea in plain English (e.g. "buy EURUSD 15min when RSI < 30, sell when RSI > 70"). symbol: optional pair to constrain the match (EURUSD, USDJPY, GBPUSD, USDCHF, USDCAD, AUDUSD, NZDUSD). timeframe: optional granularity to constrain the match (1min/5min/15min/1h). Returns: dict with: - match: the best existing strategy, or null. When present: {community_id, title, username, wr, pf, ret, n_trades, symbol, timeframe}. Pass community_id to one_shot to deploy it unchanged. - description: echoed back â pass as one_shot(prompt=...) to generate fresh. - suggestion: a ready-to-show sentence offering the user the choice.

읽기 전용 외부 접근 가능 멱등성

입력 스키마

{'type': 'object', 'title': 'find_strategyArguments', 'required': ['description'], 'properties': {'symbol': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Symbol', 'default': None}, 'timeframe': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Timeframe', 'default': None}, 'description': {'type': 'string', 'title': 'Description'}}}

출력 스키마

{'type': 'object', 'title': 'find_strategyDictOutput', 'additionalProperties': True}

generate_strategy

Generate Strategy Code (no training)

Generate Python strategy code (no training/deploy). Use when the user wants raw code. Args: features: NL description of features (e.g. "RSI 14, Bollinger Bands"). signals: NL description of signal logic (e.g. "Buy when RSI < 30"). model: ML model name (default Random Forest). risk: NL risk rules (e.g. "0.5% stop loss"). description: Optional one-line summary; treated as PRIMARY USER REQUEST. symbol: Currency pair the code should target. One of: EURUSD, USDJPY, GBPUSD, USDCHF, USDCAD, AUDUSD, NZDUSD. Default EURUSD. timeframe: Candle granularity. One of: 1min, 5min, 15min, 1h. Default 15min. claude_model: "sonnet" (default) or "haiku" (faster, higher daily cap).

외부 접근 가능

입력 스키마

{'type': 'object', 'title': 'generate_strategyArguments', 'properties': {'risk': {'type': 'string', 'title': 'Risk', 'default': ''}, 'model': {'type': 'string', 'title': 'Model', 'default': 'Random Forest'}, 'symbol': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Symbol', 'default': None}, 'signals': {'type': 'string', 'title': 'Signals', 'default': ''}, 'features': {'type': 'string', 'title': 'Features', 'default': ''}, 'timeframe': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Timeframe', 'default': None}, 'description': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Description', 'default': None}, 'claude_model': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Claude Model', 'default': None}}}

출력 스키마

{'type': 'object', 'title': 'generate_strategyDictOutput', 'additionalProperties': True}

get_deploy_result

Get Deploy Result

Wait for a `one_shot` deploy to finish and return its final result. `one_shot` returns a job_token immediately and the LIVE CARD already streams progress and renders the interactive backtest chart itself. Call this ONCE with the token to get the final numbers as TEXT so you can summarize them â it does NOT render another card (no need for get_model_chart). It BLOCKS until the deploy finishes (or ~2.5 min); on timeout it returns ok:false + pending:true â call it again with the same token. IMPORTANT: if `source == "community"`, the deploy used a PRE-EXISTING strategy by `@author` â tell the user that, share the `live_url` as the Live dashboard link, and ask whether they'd like to GENERATE A CUSTOM strategy instead. Use the `note` field as your guide. Args: job_token: the token returned by `one_shot`. Returns: dict with: ok, stem, model, live_url, symbol, timeframe, channels (list), stats:{ret, wr, pf, n, mdd} (out-of-sample test-split metrics â SHOW THESE), source ("community" | "generated"), author (community username if any), author_url + strategy_url (render @author and "pre-existing strategy" as those Markdown links), community_id, suggest_custom (bool), and note (a ready instruction â follow it). On failure: {ok:false, error} (or {pending:true}).

읽기 전용 외부 접근 가능 멱등성

입력 스키마

{'type': 'object', 'title': 'get_deploy_resultArguments', 'required': ['job_token'], 'properties': {'job_token': {'type': 'string', 'title': 'Job Token'}}}

출력 스키마

{'type': 'object', 'title': 'get_deploy_resultDictOutput', 'additionalProperties': True}

get_model_chart

Show Backtest Chart (equity + trades)

Visualize a trained model's backtest â a cumulative-return chart + trade log + stats. Use after `one_shot` / `list_models` with the model's `stem` to SHOW the user how it traded (the "is it actually any good" view). In ChatGPT this renders an interactive widget. In Claude, render an interactive **artifact** from this tool's structured output: a line chart of the cumulative return plus a table of the trades. Args: stem: The model stem (e.g. "14_EURUSD_15min_Model_24") from `list_models` / `one_shot`. Returns: dict with: ok, stem, symbol, timeframe, stats {ret, wr, pf, n, mdd, sharpe}, and trades [{type, entry_time, exit_time, entry_price, exit_price, pnl, pnl_pct, exit_reason, period}] (most recent ~200). exit_reason is one of TP / SL / close_only / signal / end. ret/mdd/wr are fractions; pnl_pct is percent.

읽기 전용 외부 접근 가능 멱등성

입력 스키마

{'type': 'object', 'title': 'get_model_chartArguments', 'required': ['stem'], 'properties': {'stem': {'type': 'string', 'title': 'Stem'}}}

출력 스키마

{'type': 'object', 'title': 'get_model_chartDictOutput', 'additionalProperties': True}

get_quote

Get Current Price (G7 FX quote)

Get the latest price for a G7 FX pair â a quick "what's it at now" check. Useful for context before deploying a strategy. The price is the close of the most recent 1-minute bar from the platform's market feed (not a raw live tick); FX markets close on weekends, so the `stale` flag marks a bar that is more than 15 minutes old. Args: symbol: G7 pair â one of EURUSD, USDJPY, GBPUSD, USDCHF, USDCAD, AUDUSD, NZDUSD. Default EURUSD. Returns: dict with: symbol, price (latest close), time (bar timestamp, UTC), change + change_pct (vs the prior 1-min bar), stale (bool).

읽기 전용 외부 접근 가능 멱등성

입력 스키마

{'type': 'object', 'title': 'get_quoteArguments', 'properties': {'symbol': {'type': 'string', 'title': 'Symbol', 'default': 'EURUSD'}}}

출력 스키마

{'type': 'object', 'title': 'get_quoteDictOutput', 'additionalProperties': True}

get_strategy_code

Get Community Strategy Code

Get the actual Python code behind a community leaderboard strategy. Use after `browse_community`: pass an entry's `id` here to read its real `feature_engineering()` + `strategy_config()` source so the user can inspect or tweak it. To deploy it unchanged, pass the same id to `one_shot` as `community_id`. Read-only, no signup needed. Args: community_id: The `id` of a community entry (from `browse_community`). Returns: dict with: id, title, username, description, symbol, timeframe, metrics {total_ret, win_rate, profit_factor, n_trades, mdd, sharpe_strat}, and `code` (the full Python source). SHOW the code to the user, and offer to deploy it via one_shot(community_id=...) or tweak it first.

읽기 전용 외부 접근 가능 멱등성

입력 스키마

{'type': 'object', 'title': 'get_strategy_codeArguments', 'required': ['community_id'], 'properties': {'community_id': {'type': 'integer', 'title': 'Community Id'}}}

출력 스키마

{'type': 'object', 'title': 'get_strategy_codeDictOutput', 'additionalProperties': True}

link_account

Link My QuantifyMe Account

Link this chat to the user's existing QuantifyMe account. Call this when the user says they already have a QuantifyMe account, or asks why their models are missing / where a model went, or wants what they deploy here to show up in their own dashboard. By default this connector works with NO signup: it mints an anonymous trial account per chat, so models deployed here belong to that throwaway identity rather than to the user's real one. This returns a short-lived URL; once the user opens it and approves, every later call in THIS chat acts as their account and deploys land in their own model list. Give the user the `link_url` to open. Nothing else is required from them.

읽기 전용 외부 접근 가능

입력 스키마

{'type': 'object', 'title': 'link_accountArguments', 'properties': {}}

출력 스키마

{'type': 'object', 'title': 'link_accountDictOutput', 'additionalProperties': True}

list_deployed

List Deployed Live Models

List the user's currently deployed (live) models.

읽기 전용 외부 접근 가능 멱등성

입력 스키마

{'type': 'object', 'title': 'list_deployedArguments', 'properties': {}}

출력 스키마

{'type': 'object', 'title': 'list_deployedDictOutput', 'additionalProperties': True}

list_models

List Trained Models

List the user's trained models with pre-computed train/test stats.

읽기 전용 외부 접근 가능 멱등성

입력 스키마

{'type': 'object', 'title': 'list_modelsArguments', 'properties': {}}

출력 스키마

{'type': 'object', 'title': 'list_modelsDictOutput', 'additionalProperties': True}

one_shot

Deploy Strategy (generate + backtest + go live)

End-to-end deploy: generate strategy â train â deploy live. One of `prompt` (free-form NL), `preset` (curated winning strategy), or `community_id` (copy a published community strategy) is required. If more than one is passed, precedence is community_id > preset > prompt. Args: prompt: Natural-language strategy description (e.g. "Buy when RSI < 30, sell > 70"). symbol: Currency pair to backtest on. One of: EURUSD, USDJPY, GBPUSD, USDCHF, USDCAD, AUDUSD, NZDUSD. Default EURUSD. timeframe: Candle granularity. One of: 1min, 5min, 15min, 1h. Default 15min. claude_model: Which Claude variant to use for code generation. "sonnet" (default â best quality, 1/day free) or "haiku" (faster, 3/day free). Ignored when `preset` is set (no generation needed). preset: Curated winning-strategy slug. Skips Claude generation entirely â deploys a pre-saved strategy known to backtest well on the chosen symbol. Available slugs: ema_cross_fast, momentum, scalper_stack, sma_only, trend_ema, volatility, bb_squeeze, all_mix, pivot_kid_ema. Not every slug exists for every symbol â call list_models afterwards to confirm what deployed. community_id: Copy-trade a published community strategy. Pass the `id` of an entry from `browse_community`. Loads that exact strategy code, skips Claude generation, then trains + deploys it. `symbol`/`timeframe` still apply to the backtest+deploy. webhook_url: Optional webhook to receive live signals. telegram_chat_id: Optional Telegram chat ID for signal delivery. Returns IMMEDIATELY (the deploy runs in the background so the live card can stream progress) with: - job_token (str): pass to get_deploy_result to fetch the final result. - poll_url (str): the card polls this for live progress; you can ignore it. - pending (bool): always true here â the deploy is still running. - symbol, timeframe (str). Call this EXACTLY ONCE per request. Pass the user's words as `prompt`; do not pre-pick presets/community strategies â the server routes (vague â a proven community strategy, specific rules â a fresh generation). NEXT STEP (always): call get_deploy_result(job_token) ONCE â it blocks until the deploy finishes and returns the out-of-sample stats + `stem` + `source`/`author` as TEXT so you can summarize. The live card already shows the chart, so you do NOT need get_model_chart. If source='community', tell the user it used a pre-existing strategy by @author and offer to generate a custom one.

파괴적 작업 외부 접근 가능

입력 스키마

{'type': 'object', 'title': 'one_shotArguments', 'properties': {'preset': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Preset', 'default': None}, 'prompt': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Prompt', 'default': None}, 'symbol': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Symbol', 'default': None}, 'timeframe': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Timeframe', 'default': None}, 'webhook_url': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Webhook Url', 'default': None}, 'claude_model': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Claude Model', 'default': None}, 'community_id': {'anyOf': [{'type': 'integer'}, {'type': 'null'}], 'title': 'Community Id', 'default': None}, 'telegram_chat_id': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Telegram Chat Id', 'default': None}}}

출력 스키마

{'type': 'object', 'title': 'one_shotDictOutput', 'additionalProperties': True}

stream_test

Live Streaming Diagnostic

Diagnostic: test whether LIVE data streaming works in this client. Renders a widget with three panels â a JS timer (baseline), a WebSocket to the live price feed, and an HTTP poll of /quote â each showing a live value + status, so you can see exactly which streaming mechanisms the client's widget sandbox actually permits. Use when a live/ticking chart isn't moving. Args: symbol: G7 pair to stream (default EURUSD).

읽기 전용 외부 접근 가능 멱등성

입력 스키마

{'type': 'object', 'title': 'stream_testArguments', 'properties': {'symbol': {'type': 'string', 'title': 'Symbol', 'default': 'EURUSD'}}}

출력 스키마

{'type': 'object', 'title': 'stream_testDictOutput', 'additionalProperties': True}

top_up

Top Up Credits with Crypto

Fund your QuantifyMe credits with crypto (USDC) â no signup, no human, no card. The agent-native funding rail. SIMULATED in this build (no real charge) and capped at $100 for the POC. Returns your new credit balance.

외부 접근 가능

입력 스키마

{'type': 'object', 'title': 'top_upArguments', 'required': ['amount_usd'], 'properties': {'amount_usd': {'type': 'number', 'title': 'Amount Usd'}}}

출력 스키마

{'type': 'object', 'title': 'top_upDictOutput', 'additionalProperties': True}

추가됨

                            stream_test
                        

2026년 9월 17일 7:57 AM

추가됨

                            get_model_chart
                        

2026년 9월 17일 7:57 AM

추가됨

                            get_quote
                        

2026년 9월 17일 7:57 AM

추가됨

                            get_strategy_code
                        

2026년 9월 17일 7:57 AM

추가됨

                            find_strategy
                        

2026년 9월 17일 7:57 AM

추가됨

                            browse_community
                        

2026년 9월 17일 7:57 AM

추가됨

                            generate_strategy
                        

2026년 9월 17일 7:57 AM

추가됨

                            top_up
                        

2026년 9월 17일 7:57 AM

추가됨

                            list_deployed
                        

2026년 9월 17일 7:57 AM

추가됨

                            list_models
                        

2026년 9월 17일 7:57 AM

추가됨

                            link_account
                        

2026년 9월 17일 7:57 AM

추가됨

                            get_deploy_result
                        

2026년 9월 17일 7:57 AM

추가됨

                            one_shot
                        

2026년 9월 17일 7:57 AM

서버 정보

버전

1.0.0

전송 방식

Streamable HTTP

도구

지연 시간

3571 ms

마지막 스캔

2026년 10월 1일 2:52 AM

최초 확인

2026년 9월 11일 3:27 PM

엔드포인트

https://mcp.quantifyme.ai/mcp

최근 스캔

성공

2026년 10월 1일 2:52 AM

성공

2026년 9월 29일 3:00 AM

성공

2026년 9월 27일 2:51 AM

성공

2026년 9월 25일 3:00 AM

성공

2026년 9월 23일 2:51 AM

성공

2026년 9월 21일 2:58 AM

성공

2026년 9월 19일 2:49 AM

성공

2026년 9월 17일 12:56 PM

성공

2026년 9월 17일 7:57 AM

quantifyme

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