About Polymarket MCP Server
Polymarket MCP Server exposes Polymarket's Gamma Markets API data to AI assistants. Its configurable tool set covers markets, events, order books, trades, and historical data.
Key features
- 01Filter market and event listings
- 02Retrieve market and event details
- 03Search markets by keyword
- 04Access order books and recent trades
- 05Retrieve historical market data
- 06Select which tools are available
Use cases
- 01Review prediction market listings
- 02Inspect a specific event or market
- 03Check recent trades and order books
- 04Examine historical market data
MCP support
It provides configurable tools through MCP for clients to query Polymarket market and event data.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEPolymarket MCP Server
A Model Context Protocol (MCP) server for Polymarket's Gamma Markets API.
This provides access to Polymarket's prediction markets and market data through standardized MCP interfaces, allowing AI assistants to query market data and analyze prediction markets.
Features
-
Market and Event data access
- List all available markets and events with extensive filtering options
- Get detailed market and event information
- Search markets by keyword
- Get order book data
- View recent trades
- Get historical market data
-
Docker containerization support
-
Provide interactive tools for AI assistants
The list of tools is configurable, so you can choose which tools you want to make available to the MCP client. This is useful if you don't use certain functionality or if you don't want to take up too much of the context window.
Usage with Claude Desktop
Docker Setup
To use the containerized server with Claude Desktop, add this to your Claude Desktop configuration:
{
"mcpServers": {
"polymarket": {
"command": "docker",
"args": [
"run",
"--rm",
"-i",
"-e", "GAMMA_API_URL",
"-e", "GAMMA_REQUIRES_AUTH",
"polymarket-mcp-server"
],
"env": {
"GAMMA_API_URL": "https://gamma-api.polymarket.com",
"GAMMA_REQUIRES_AUTH": "false"
}
}
}
}
Note: You'll need to build the Docker image first with
docker build -t polymarket-mcp-server .
UV Setup (Alternative Method)
If you prefer not to use Docker, you can use uv to run the server directly:
- Create and configure a
.envfile in the project root directory:
# Copy the template
cp .env.template .env
# Edit the file to add your configuration
nano .env
Example .env content:
# Polymarket Gamma API Configuration
GAMMA_API_URL=https://gamma-api.polymarket.com
GAMMA_REQUIRES_AUTH=false
- Add the server configuration to your Claude Desktop configuration:
{
"mcpServers": {
"polymarket": {
"command": "/usr/local/bin/uv", // Use the full path to your uv installation
"args": [
"run",
"-m", "polymarket_mcp_server.main"
],
"cwd": "<full path to polymarket-mcp directory>",
"env": {
"GAMMA_API_URL": "https://gamma-api.polymarket.com",
"GAMMA_REQUIRES_AUTH": "false"
}
}
}
}
Note: If you see
Error: spawn uv ENOENTin Claude Desktop, you may need to specify the full path touvor set the environment variableNO_UV=1in the configuration.
Development
Contributions are welcome! Please open an issue or submit a pull request if you have any suggestions or improvements.
This project uses uv to manage dependencies. Install uv following the instructions for your platform:
curl -LsSf https://astral.sh/uv/install.sh | sh
You can then create a virtual environment and install the dependencies with:
uv venv
source .venv/bin/activate # On Unix/macOS
.venv\Scripts\activate # On Windows
uv pip install -e .
Environment Variables Support
The server loads environment variables from a .env file in the project root directory if present. Copy .env.template to .env and adjust the values as needed.
Project Structure
The project has been organized with a src directory structure:
polymarket-mcp/
├── src/
│ └── polymarket_mcp_server/
│ ├── __init__.py # Package initialization
│ ├── server.py # MCP server implementation
│ └── main.py # Main application logic
├── Dockerfile # Docker configuration
├── .dockerignore # Docker ignore file
├── .env.template # Template for environment variables
├── pyproject.toml # Project configuration
└── README.md # This file
Testing
The project includes a comprehensive test suite that ensures functionality and helps prevent regressions.
Run the tests with pytest:
# Install development dependencies
uv pip install -e ".[dev]"
# Run the tests
pytest
# Run with coverage report
pytest --cov=src --cov-report=term-missing
Tests are organized into:
- Server functionality tests
- Main application tests
- Error handling tests
When adding new features, please also add corresponding tests.
Available Tools
| Tool | Category | Description |
|---|---|---|
get_markets | Market Data | Get a list of all available markets with comprehensive filtering options |
get_market_by_id | Market Data | Get detailed information about a specific market |
get_order_book | Market Data | [EXPERIMENTAL] Get the current order book for a market |
get_recent_trades | Market Data | [EXPERIMENTAL] Get latest trades for a market |
get_market_history | Market Data | [EXPERIMENTAL] Get historical market data |
search_markets | Market Data | Search for markets by keyword using slug filtering |
get_events | Event Data | Get a list of all available events with comprehensive filtering options |
get_event_by_id | Event Data | Get detailed information about a specific event |
License
MIT
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.