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2025-04-13

Un servidor MCP para interactuar con los mercados de predicción de Kalshi

3 years

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MCP Server Kalshi

This is an MCP server for the Kalshi REST API

Configuration

Claud Desktop

Setting up with UVX
"mcpServers": {
  "kalshi": {
    "command": "uvx",
    "args": ["mcp-server-kalshi"],
    "env": {
        "KALSHI_PRIVATE_KEY_PATH": "PATH TO YOUR RSA KEY FILE",
        "KALSHI_API_KEY": "<YOUR KALSHI API KEY>",
        "BASE_URL": "https://api.elections.kalshi.com"
    }
  }
}
Setting up with Docker
  1. Build the container from root directory docker build -t mcp-server-kalshi .

  2. Configure client to run the container (ensure the bind command gives the container access to your rsa key files)

"mcpServers": {
  "kalshi": {
    "command": "docker",
    "args": ["run", "--rm", "-i", "--mount", "type=bind,src=/Users/username,dst=/Users/username", "-e", "KALSHI_PRIVATE_KEY_PATH", "-e", "KALSHI_API_KEY","-e", "BASE_URL", "mcp-server-kalshi"],
    "env": {
        "KALSHI_PRIVATE_KEY_PATH": "PATH TO YOUR RSA KEY FILE",
        "KALSHI_API_KEY": "<YOUR KALSHI API KEY>",
        "BASE_URL": "https://api.elections.kalshi.com"
    }
  }
}

Local Development

  1. Create a .env file in the root directory with the following variables

    • BASE_URL The kalshi API URL
    • KALSHI_API_KEY The API key for the corresponding environment
    • KALSHI_PRIVATE_KEY_PATH A filepath to a file containing your Kalshi RSA private key
  2. Install deps via uv pip install -e . Dev deps can be installed with uv pip install -e .[dev]

  3. Run with uv run start

Getting Kalshi API Creds

To get Kalshi API creds, follow the instrictions here

Getting a Test Account

You may want to run the server against a kalshi demo account. To get an account, follow the instructions here

Then, set BASE_URL=https://demo-api.kalshi.co for this MCP server and update your KALSHI_API_KEY and KALSHI_PRIVATE_KEY_PATH to point towards credentials generated in the testing environment

UVX

To run in MCP inspector

npx @modelcontextprotocol/inspector uv --directory /path/to/your/mcp-server-kalshi run start

To run in claud desktop, update your MCP config to:

{
    "mcpServers": {
        "kalshi": {
            "command": "uv",
            "args": [ 
            "--directory",
            "/<path to repo root directory>",
            "run",
            "start"
            ],
            "env": {
                "KALSHI_PRIVATE_KEY_PATH": "PATH TO YOUR RSA KEY FILE",
                "KALSHI_API_KEY": "<YOUR KALSHI API KEY>",
                "BASE_URL": "https://api.elections.kalshi.com"
            }
        }
    }
}

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    Reviews

    1 (1)
    Avatar
    user_YHkKBB8K
    2025-04-16

    I've been using the QGISMCP - QGIS Model Context Protocol Integration by jjsantos01 and it's been transformative for my GIS projects. The seamless integration with QGIS enhances workflow efficiency and the intuitive interface makes complex data management straightforward. Highly recommend checking it out at https://mcp.so/server/qgis_mcp/jjsantos01!