LLMQuant/data-mcp: The knowledge harness for AI‑native finance — MCP server for LLMQuant Data. · GitHub

The knowledge harness for AI‑native finance.
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Context engineering meets financial data — structured for agent context, not human browsing.

• What It Does
• Available Tools
• Try It Out
• Quick Install (Prompt)
• Client Setup
• Remote / Hosted MCP
• Environment Variables
• Roadmap
• See Also
• Contributing
• License

This is an MCP server for LLMQuant Data. It connects any AI agent to financial data — wiki articles, research papers, crypto & equity prices, prediction markets, macro indicators, SEC filings, and more — through the Model Context Protocol.

Configure once — every agent in your stack gets the data.

* An unsupported ETF ticker returns 200 with an explicit coverage notice and 0 credits — you are only charged the 1 credit when holdings are actually returned.

Prediction Markets tools follow an event-first flow: use polymarket_event_search first for natural-language discovery, use polymarket_event_browse only for list/exact-filter requests, then read a selected event, read a market, and request price history for an outcome token.

More data products (company fundamentals, earnings transcripts, etc.) are on the roadmap.

Four ways to access each data product:

Launch the MCP Inspector to explore tools interactively in your browser:

export LLMQUANT_API_KEY=your_api_key
npx @modelcontextprotocol/inspector npx -y @llmquant/data-mcp

The fastest way: drop this prompt into Claude Code, Cursor, Codex CLI, Gemini CLI, or any MCP-enabled agent. The agent will read this README and run the right setup for its runtime.

Install the LLMQuant data-mcp server in this environment by following https://github.com/LLMQuant/data-mcp

Prefer to set it up by hand? See Client Setup below.

claude mcp add llmquant-data \
  -e LLMQUANT_API_KEY=your_api_key \
  -- npx -y @llmquant/data-mcp

Add to .cursor/mcp.json (project) or ~/.cursor/mcp.json (global):

{
  "mcpServers": {
    "llmquant-data": {
      "command": "npx",
      "args": ["-y", "@llmquant/data-mcp"],
      "env": {
        "LLMQUANT_API_KEY": "your_api_key"
      }
    }
  }
}

codex mcp add llmquant-data \
  --env LLMQUANT_API_KEY=your_api_key \
  -- npx -y @llmquant/data-mcp

gemini mcp add -s user \
  -e LLMQUANT_API_KEY=your_api_key \
  llmquant-data \
  npx -y @llmquant/data-mcp

Any client supporting stdio transport can use this JSON config:

{
  "mcpServers": {
    "llmquant-data": {
      "command": "npx",
      "args": ["-y", "@llmquant/data-mcp"],
      "env": {
        "LLMQUANT_API_KEY": "your_api_key"
      }
    }
  }
}

@llmquant/data-mcp keeps local stdio as the default setup path. Signed-in LLMQuant users can also generate a hosted Remote MCP connector URL from the dashboard. Hosted connectors are useful when your MCP client supports remote connectors and you do not want to run a local Node.js process.

In the LLMQuant dashboard, open Connect and generate a Remote MCP URL.

https://mcp.llmquantdata.com/u/lqd_mcp_.../mcp

Paste the full URL into Claude's custom connector flow. The hosted URL is separate from your local LLMQUANT_API_KEY and can be revoked from the dashboard.

• Streamable HTTP transport (remote MCP without local Node.js)
• OAuth connector flow for Claude Connectors Directory
• More data products — company fundamentals, earnings transcripts
• Agent skills companion catalog (LLMQuant/skills)
• Integration guides for more agent frameworks

Have a feature request? Open an issue or email us at contact@llmquant.com.

• Awesome Trading Agents — community-curated agent recipes that turn data-mcp tools into end-to-end research workflows (equity research, macro briefings, smart-money digests).
• Documentation — full API reference, MCP setup guides, and credit policy.

This repository is a read-only mirror. We do not accept pull requests.

Found a bug or have a feature request? Please open an issue — we actively triage and respond.

MIT