MCP-Server-Kalshi
Un serveur MCP pour interagir avec les marchés de prédiction Kalshi
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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
-
Build the container from root directory
docker build -t mcp-server-kalshi . -
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
-
Create a
.envfile in the root directory with the following variables-
BASE_URLThe kalshi API URL -
KALSHI_API_KEYThe API key for the corresponding environment -
KALSHI_PRIVATE_KEY_PATHA filepath to a file containing your Kalshi RSA private key
-
-
Install deps via
uv pip install -e .Dev deps can be installed withuv pip install -e .[dev] -
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
user_YHkKBB8K
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!