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PolyMarket

berlinbra/polymarket-mcp
138
Summary

Wraps the PolyMarket prediction markets API to pull real-time betting odds and market data directly into Claude. You get four operations: listing active markets with status filters, fetching detailed market info including volume and resolution dates, grabbing current prices and probability percentages for outcomes, and pulling historical price charts across different timeframes. Useful when you need to analyze political betting markets, check event probabilities, or build trading analysis workflows. Handles rate limiting and includes proper error handling for API timeouts.

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PolyMarket MCP Server

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A Model Context Protocol (MCP) server that provides access to prediction market data through the PolyMarket API. This server implements a standardized interface for retrieving market information, prices, and historical data from prediction markets.

PolyMarket Server MCP server

MseeP.ai Security Assessment Badge

Features

  • Real-time prediction market data with current prices and probabilities
  • Detailed market information including categories, resolution dates, and descriptions
  • Historical price and volume data with customizable timeframes (1d, 7d, 30d, all)
  • Built-in error handling and rate limit management
  • Clean data formatting for easy consumption

Installation

Installing via Smithery

To install PolyMarket Predictions for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install polymarket_mcp --client claude

Claude Desktop

  • On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json
  • On Windows: %APPDATA%/Claude/claude_desktop_config.json
Development/Unpublished Servers Configuration
    "mcpServers": {
        "polymarket-mcp": {
            "command": "uv",
            "args": [
            "--directory",
            "/Users/{INSERT_USER}/YOUR/PATH/TO/polymarket-mcp",
            "run",
            "polymarket-mcp" //or src/polymarket_mcp/server.py
            ],
            "env": {
                "KEY": "<insert poly market api key>",
                "FUNDER": "<insert polymarket wallet address>"
            }
        }
    }

Running Locally

  1. Clone the repository and install dependencies:

Install Libraries

uv pip install -e .

Running

After connecting Claude client with the MCP tool via json file and installing the packages, Claude should see the server's mcp tools:

You can run the sever yourself via: In polymarket-mcp repo:

uv run src/polymarket_mcp/server.py

*if you want to run the server inspector along with the server:

npx @modelcontextprotocol/inspector uv --directory C:\\Users\\{INSERT_USER}\\YOUR\\PATH\\TO\\polymarket-mcp run src/polymarket_mcp/server.py
  1. Create a .env file with your PolyMarket API key:
Key=your_api_key_here
Funder=poly market wallet address

After connecting Claude client with the MCP tool via json file, run the server: In alpha-vantage-mcp repo: uv run src/polymarket_mcp/server.py

Available Tools

The server implements four tools:

  • get-market-info: Get detailed information about a specific prediction market
  • list-markets: List available prediction markets with filtering options
  • get-market-prices: Get current prices and trading information
  • get-market-history: Get historical price and volume data

get-market-info

Input Schema:

{
    "market_id": {
        "type": "string",
        "description": "Market ID or slug"
    }
}

Example Response:

Title: Example Market
Category: Politics
Status: Open
Resolution Date: 2024-12-31
Volume: $1,234,567.89
Liquidity: $98,765.43
Description: This is an example prediction market...
---

list-markets

Input Schema:

{
    "status": {
        "type": "string",
        "description": "Filter by market status",
        "enum": ["open", "closed", "resolved"]
    },
    "limit": {
        "type": "integer",
        "description": "Number of markets to return",
        "default": 10,
        "minimum": 1,
        "maximum": 100
    },
    "offset": {
        "type": "integer",
        "description": "Number of markets to skip (for pagination)",
        "default": 0,
        "minimum": 0
    }
}

Example Response:

Available Markets:

ID: market-123
Title: US Presidential Election 2024
Status: Open
Volume: $1,234,567.89
---

ID: market-124
Title: Oscar Best Picture 2024
Status: Open
Volume: $234,567.89
---

get-market-prices

Input Schema:

{
    "market_id": {
        "type": "string",
        "description": "Market ID or slug"
    }
}

Example Response:

Current Market Prices for US Presidential Election 2024

Outcome: Democratic
Price: $0.6500
Probability: 65.0%
---

Outcome: Republican
Price: $0.3500
Probability: 35.0%
---

get-market-history

Input Schema:

{
    "market_id": {
        "type": "string",
        "description": "Market ID or slug"
    },
    "timeframe": {
        "type": "string",
        "description": "Time period for historical data",
        "enum": ["1d", "7d", "30d", "all"],
        "default": "7d"
    }
}

Example Response:

Historical Data for US Presidential Election 2024
Time Period: 7d

Time: 2024-01-20T12:00:00Z
Price: $0.6500
Volume: $123,456.78
---

Time: 2024-01-19T12:00:00Z
Price: $0.6300
Volume: $98,765.43
---

Error Handling

The server includes comprehensive error handling for various scenarios:

  • Rate limiting (429 errors)
  • Invalid API keys (403 errors)
  • Invalid market IDs (404 errors)
  • Network connectivity issues
  • API timeout conditions (30-second timeout)
  • Malformed responses

Error messages are returned in a clear, human-readable format.

Prerequisites

  • Python 3.9 or higher
  • httpx>=0.24.0
  • mcp-core
  • python-dotenv>=1.0.0

Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

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UpdatedFeb 14, 2026
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