MCP Radar
Serveur MCP

quantifyme

ai.quantifyme/quantifyme
Finance et investissement Public et accessible MCP 2025-11-25

Ce que fait ce MCP

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

Capacités

Outils

13 outils
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 — 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 — 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.
Lecture seule Accès externe Idempotent
Schéma d’entrée 
{'type': 'object', 'title': 'browse_communityArguments', 'properties': {'sort': {'type': 'string', 'title': 'Sort', 'default': 'composite'}, 'limit': {'type': 'integer', 'title': 'Limit', 'default': 20}}}
Schéma de sortie 
{'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 — deploy the existing one, or generate a fresh custom one. Mirrors the quantifyme.ai landing experience: "Found <X> by @<author> (WR/PF) — 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: • Use it → one_shot(community_id=<match.community_id>) — deploys the exact proven strategy (free, no generation). • Generate fresh → one_shot(prompt="<their description>") — 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 — pass as one_shot(prompt=...) to generate fresh. - suggestion: a ready-to-show sentence offering the user the choice.
Lecture seule Accès externe Idempotent
Schéma d’entrée 
{'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'}}}
Schéma de sortie 
{'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).
Accès externe
Schéma d’entrée 
{'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}}}
Schéma de sortie 
{'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 — 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 — call it again with the same token. IMPORTANT: if `source == "community"`, the deploy used a PRE-EXISTING strategy by `@author` — 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 — 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 — follow it). On failure: {ok:false, error} (or {pending:true}).
Lecture seule Accès externe Idempotent
Schéma d’entrée 
{'type': 'object', 'title': 'get_deploy_resultArguments', 'required': ['job_token'], 'properties': {'job_token': {'type': 'string', 'title': 'Job Token'}}}
Schéma de sortie 
{'type': 'object', 'title': 'get_deploy_resultDictOutput', 'additionalProperties': True}
get_model_chart
Show Backtest Chart (equity + trades)
Visualize a trained model's backtest — 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.
Lecture seule Accès externe Idempotent
Schéma d’entrée 
{'type': 'object', 'title': 'get_model_chartArguments', 'required': ['stem'], 'properties': {'stem': {'type': 'string', 'title': 'Stem'}}}
Schéma de sortie 
{'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 — 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 — 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).
Lecture seule Accès externe Idempotent
Schéma d’entrée 
{'type': 'object', 'title': 'get_quoteArguments', 'properties': {'symbol': {'type': 'string', 'title': 'Symbol', 'default': 'EURUSD'}}}
Schéma de sortie 
{'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.
Lecture seule Accès externe Idempotent
Schéma d’entrée 
{'type': 'object', 'title': 'get_strategy_codeArguments', 'required': ['community_id'], 'properties': {'community_id': {'type': 'integer', 'title': 'Community Id'}}}
Schéma de sortie 
{'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.
Lecture seule Accès externe
Schéma d’entrée 
{'type': 'object', 'title': 'link_accountArguments', 'properties': {}}
Schéma de sortie 
{'type': 'object', 'title': 'link_accountDictOutput', 'additionalProperties': True}
list_deployed
List Deployed Live Models
List the user's currently deployed (live) models.
Lecture seule Accès externe Idempotent
Schéma d’entrée 
{'type': 'object', 'title': 'list_deployedArguments', 'properties': {}}
Schéma de sortie 
{'type': 'object', 'title': 'list_deployedDictOutput', 'additionalProperties': True}
list_models
List Trained Models
List the user's trained models with pre-computed train/test stats.
Lecture seule Accès externe Idempotent
Schéma d’entrée 
{'type': 'object', 'title': 'list_modelsArguments', 'properties': {}}
Schéma de sortie 
{'type': 'object', 'title': 'list_modelsDictOutput', 'additionalProperties': True}
one_shot
Deploy Strategy (generate + backtest + go live)
End-to-end deploy: generate strategy → train → 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 — 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 — 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 — 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 — 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 — the server routes (vague → a proven community strategy, specific rules → a fresh generation). NEXT STEP (always): call get_deploy_result(job_token) ONCE — 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.
Destructif Accès externe
Schéma d’entrée 
{'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}}}
Schéma de sortie 
{'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 — a JS timer (baseline), a WebSocket to the live price feed, and an HTTP poll of /quote — 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).
Lecture seule Accès externe Idempotent
Schéma d’entrée 
{'type': 'object', 'title': 'stream_testArguments', 'properties': {'symbol': {'type': 'string', 'title': 'Symbol', 'default': 'EURUSD'}}}
Schéma de sortie 
{'type': 'object', 'title': 'stream_testDictOutput', 'additionalProperties': True}
top_up
Top Up Credits with Crypto
Fund your QuantifyMe credits with crypto (USDC) — 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.
Accès externe
Schéma d’entrée 
{'type': 'object', 'title': 'top_upArguments', 'required': ['amount_usd'], 'properties': {'amount_usd': {'type': 'number', 'title': 'Amount Usd'}}}
Schéma de sortie 
{'type': 'object', 'title': 'top_upDictOutput', 'additionalProperties': True}
Historique

Modifications récentes des outils

Ajouté
stream_test
17 September 2026 07:57
Ajouté
get_model_chart
17 September 2026 07:57
Ajouté
get_quote
17 September 2026 07:57
Ajouté
get_strategy_code
17 September 2026 07:57
Ajouté
find_strategy
17 September 2026 07:57
Ajouté
browse_community
17 September 2026 07:57
Ajouté
generate_strategy
17 September 2026 07:57
Ajouté
top_up
17 September 2026 07:57
Ajouté
list_deployed
17 September 2026 07:57
Ajouté
list_models
17 September 2026 07:57
Ajouté
link_account
17 September 2026 07:57
Ajouté
get_deploy_result
17 September 2026 07:57
Ajouté
one_shot
17 September 2026 07:57
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