TA-Lib MCP Server

Technical analysis indicators MCP server for Model Context Protocol.

Quick Start

# Install dependencies uv sync --dev # Copy logging configuration cp logging.conf.example logging.conf # Run server with STDIO transport uv run python -m mcp_talib.cli --transport stdio # Run server with HTTP transport uv run python -m mcp_talib.cli --transport http --host 0.0.0.0 --port 8000

Logging Configuration

The server requires a logging.conf file for configuration. Copy the example configuration:

cp logging.conf.example logging.conf

You can customize the logging levels, format, and output file in logging.conf. The server logs to console.log to maintain MCP protocol compliance.

Core Indicators: SMA, RSI, MACD
Advanced Indicators: Bollinger Bands, Stochastic, ADX
Dual Transport: Both STDIO and HTTP support
Performance: Optimized for high-volume calculations
Error Handling: Comprehensive error handling with detailed messages
Monitoring: Metrics and health endpoints

Client Configuration

Claude Desktop Integration

Create a configuration file at ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or appropriate location for your OS.
Add the MCP server configuration:

{ "mcpServers": { "talib": { "command": "uv", "args": [ "run", "python", "-m", "mcp_talib.cli", "--transport", "stdio" ], "cwd": "/path/to/mcp-talib" } } }

Restart Claude Desktop to load the TA-Lib server.
Verify installation by asking Claude: "What technical analysis tools do you have?"

HTTP Client Configuration

For HTTP transport, configure your client to connect to:

http://localhost:8000/mcp

The server supports Server-Sent Events (SSE) for real-time updates.

MCP.js Client Example

import { MCPServerClient } from '@modelcontextprotocol/client'; const client = new MCPServerClient({ name: 'talib', command: 'uv', args: ['run', 'python', '-m', 'mcp_talib.cli', '--transport', 'stdio'], cwd: process.cwd() }); // List available tools const tools = await client.listTools(); console.log('Available tools:', tools.map(t => t.name)); // Calculate SMA const smaResult = await client.callTool('calculate_sma', { close_prices: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], timeperiod: 5 }); console.log('SMA result:', smaResult);

Available Tools

The server provides the following MCP tools:

calculate_sma - Simple Moving Average
calculate_ema - Exponential Moving Average
calculate_rsi - Relative Strength Index

Documentation

See specs/001-ta-lib-mcp-server/quickstart.md for detailed usage instructions.

Development

# Run tests uv run pytest # Format code uv run black src/ tests/ uv run isort src/ tests/ # Lint code uv run ruff check src/ tests/

License

MIT

HTTP API & CLI

This project now exposes the same MCP tools as both HTTP JSON endpoints and a Typed CLI (Typer).

HTTP endpoint: POST /api/tools/{tool_name}
- Request JSON: { "close": [..], ...params } (e.g. timeperiod)
- Response JSON: { "success": true, "values": [...], "metadata": {...} }
- Example curl:

curl -s -X POST http://localhost:8000/api/tools/sma \ -H 'Content-Type: application/json' \ -d '{"close": [1,2,3,4,5], "timeperiod": 3}'

MCP endpoint remains at /mcp for MCP clients (MCP Inspector, MCP.js, etc.). The HTTP API mounts the MCP app so both APIs coexist.
CLI (Typer): src/mcp_talib/cli_tools.py
- List tools:

python -m mcp_talib.cli_tools list

Call a tool from the CLI:

python -m mcp_talib.cli_tools call sma --close '[1,2,3,4]' --timeperiod 3

Notes:

Requests are validated using Pydantic (ToolRequest / ToolResult).
The underlying indicator implementations remain the single source of truth (registered in the MCP registry) — the HTTP API and CLI call the same code so results match.
For browser clients, CORS is enabled and mcp-session-id is exposed in responses.