This MCP server facilitates interaction with Kalshi prediction markets, allowing users to search, analyze, and trade directly through Claude Desktop.
From the registry: Search, analyze, and trade Kalshi prediction markets through Claude Desktop
$ pip install kalshi-mcpPlease install the `kalshi-yakub268` MCP server into my current AI client (that's you).
Required prerequisites (do these first if not already done):
- **Kalshi API credentials** — Create API key at kalshi.com/profile/api-keys and download the RSA private key .pem file (https://kalshi.com/profile/api-keys)
- **Python 3.10+** — Python 3.10 or newer required
- **Install package** — Install via PyPI Run: `pip install kalshi-mcp`
Canonical MCP server config (stdio transport):
- command: `python`
- args: ["-m","kalshi_mcp"]
- required environment variables:
- `KALSHI_API_KEY`: Kalshi API key (example: `<your-api-key>`)
- `KALSHI_PRIVATE_KEY_PATH`: Absolute path to the Kalshi RSA private key .pem file (example: `/path/to/kalshi_private_key.pem`)
Add this MCP server to my current client's config in the correct format for you. If you need secrets or credentials I haven't provided, ASK me — do not invent values or leave raw placeholders. After adding it, tell me how to verify the server is connected.KALSHI_API_KEYrequiredYour Kalshi API keyKALSHI_PRIVATE_KEY_PATHrequiredPath to your RSA private key (.pem file)MCP server for searching Airweave collections with natural language queries.