ai.quantifyme/quantifyme
ai.quantifyme/quantifymeDescribe a trading strategy in plain English and deploy a live signal model in one call. No signup.
Tools · 11
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 req…
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 …
List the user's trained models with pre-computed train/test stats.
List the user's currently deployed (live) models.
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 descript…
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 strate…
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 land…
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()` sour…
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 platf…
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 a…
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 —…
How to use
Add to your Claude Desktop / Cursor / Cline MCP config:
{
"mcpServers": {
"ai.quantifyme/quantifyme": {
"url": "https://mcp.quantifyme.ai/mcp",
"transport": "streamable-http"
}
}
}