# Quantifyme MCP server

Source: https://glimind.com/server/mcp-registry%2Fai.quantifyme%2Fquantifyme
Registry id: `mcp-registry/ai.quantifyme/quantifyme`
Status: live (checked 2026-10-26T18:42:20.841Z)

## Measurements (30 days)

- Uptime: 99.83%
- Checks: 4930
- Outages (90 days): 34

## Install

```json
{
  "mcpServers": {
    "quantifyme-mcp-server": {
      "type": "http",
      "url": "https://mcp.quantifyme.ai/mcp"
    }
  }
}
```

Claude Code:

```sh
claude mcp add --transport http quantifyme-mcp-server https://mcp.quantifyme.ai/mcp
```

## Tools (13)

- `browse_community`: Browse the public community leaderboard of published strategies, ranked by a composite performance score (best first). No signup or key needed. Copy-trade flow:
- `find_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
- `generate_strategy`: 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"
- `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 re
- `get_model_chart`: 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 u
- `get_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 rec
- `get_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_engineerin
- `link_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 miss
- `list_deployed`: List the user's currently deployed (live) models.
- `list_models`: List the user's trained models with pre-computed train/test stats. `acting_as` names the identity listed: the linked account or a trial user (#1962).
- `one_shot`: End-to-end deploy: generate strategy → train → deploy live. One of `prompt` (free-form NL), `preset` (curated winning strategy), or `community_id` (copy a publi
- `stream_test`: Diagnostic: test whether LIVE data streaming works in this client. Renders a widget with three panels: a JS timer (baseline), the WebSocket panel (not offered: 
- `top_up`: Simulated crypto top-up for a QuantifyMe DEV server only: no money moves, so it never makes an account paid and grants at most up to the free credit cap ($100 p

Measured by Glimind (https://glimind.com): MCP handshake + tool list only, no tool is ever called. CC BY 4.0.