Trading212 Server

PyPI License: MIT Glama

Connect your AI assistant to your Trading 212 brokerage account. Ask questions about your portfolio, place trades, manage pies, and analyze dividends - all through natural language.

Works with Claude Desktop, Claude Code, ChatGPT, Gemini, Cursor, Windsurf, and any client that supports the Model Context Protocol (MCP).

Why this server?

• 32 tools covering the full Trading 212 API, plus 4 analytics tools that combine multiple API calls into actionable insights
• Smart rate limiting - reads T212's rate limit headers, auto-waits, and retries on 429 (up to 3 times). No rate limit errors leak to your AI
• Zero config - install from PyPI, add your API key, done. No Docker, no database, no Redis
• Typed responses - every tool returns structured Pydantic models, not raw JSON
• Paper trading - set ENVIRONMENT=demo to test with virtual money first

What can it do?

Analytics tools

These combine multiple API calls into single high-level responses:

• fetch_portfolio_summary - Complete snapshot: total value, P&L, cash, top holdings, allocation
• fetch_portfolio_performance - Per-position returns with dividends, best/worst performers
• fetch_dividend_summary - Income analysis grouped by ticker and month
• fetch_recent_activity - Combined timeline of trades and transactions

Quick start

Install

uvx trading212-mcp-server

Or via pip:

pip install trading212-mcp-server

Get your API credentials

From the Trading 212 app: Settings > API (Beta). You need both the API Key and Secret - the server uses Basic Auth.

Connect to Claude Desktop

Add to claude_desktop_config.json (Windows: %APPDATA%\Claude\, Mac: ~/Library/Application Support/Claude/):

{
  "mcpServers": {
    "trading212": {
      "command": "uvx",
      "args": ["trading212-mcp-server"],
      "env": {
        "TRADING212_API_KEY": "<your-api-key>",
        "TRADING212_API_SECRET": "<your-api-secret>",
        "ENVIRONMENT": "live"
      }
    }
  }
}

Connect to Claude Code

claude mcp add trading212 -- uvx trading212-mcp-server

Then set the environment variables in your shell or .env file.

Other clients (Cursor, Windsurf, ChatGPT, etc.)

Same command and env vars - configure per your client's MCP docs. Set ENVIRONMENT to demo for paper trading.

From source

git clone https://github.com/KyuRish/trading212-mcp-server.git
cd trading212-mcp-server
cp .env.example .env  # fill in your API keys
uv sync
uv run -m trading212_mcp_server.server

{
  "mcpServers": {
    "trading212": {
      "command": "uv",
      "args": ["run", "--directory", "<path-to-repo>", "-m", "trading212_mcp_server.server"],
      "env": {
        "TRADING212_API_KEY": "<your-api-key>",
        "TRADING212_API_SECRET": "<your-api-secret>",
        "ENVIRONMENT": "live"
      }
    }
  }
}

All 32 tools

Analytics (composite)

Account

Trading

Pies

Market Data

History

Compatibility

Tested with these MCP clients:

Author

Built by Rishabh Dogra.

Support

If this server saves you time, a coffee would mean a lot.

Buy Me a Coffee

License

MIT