MCP Server Kalshi vs ModelRunner

In-depth architectural comparison of the MCP Server Kalshi and ModelRunner MCP servers. Compare execution transports, security boundaries, tool capabilities, quality scores, and ready-to-paste client installation snippets for Claude, Cursor, Windsurf, and VS Code.

Which MCP Server Should You Choose?

Choose MCP Server Kalshi when:

• You need dedicated capabilities in the Finance & Fintech domain.
• You prefer local stdio subprocess transport architecture.
• Your security boundary fits: API Key required (Free / Open Source).
• You have access to required keys: KALSHI_ENV, KALSHI_API_KEY, KALSHI_PRIVATE_KEY_PATH, BASE_URL.
• Primary tools included: Market, event, and series discovery, Order book, candlestick, and trade research, Settlement rule and contract PDF extraction.

Explore MCP Server Kalshi Details

Choose ModelRunner when:

• You need dedicated capabilities in the Finance & Fintech domain.
• You prefer remote streaming HTTP/SSE transport architecture.
• Your security boundary fits: No auth required (Free / Open Source).

Explore ModelRunner Details

Feature & Specification Comparison

Specification	MCP Server Kalshi Finance & Fintech	ModelRunner Finance & Fintech
Summary	MCP server for end-to-end trading on Kalshi prediction markets: discover, research, trade.	Run 100+ AI models — image, video, audio, 3D — through one API with pay-per-use billing.
Category & Scope	Finance & Fintech	Finance & Fintech

Tools & Capabilities Breakdown

Ready-to-Paste Client Configurations

Paste either (or both) of these JSON server blocks into your client config file (e.g. claude_desktop_config.json or ~/.cursor/mcp.json).

{
  "mcpServers": {
    "mcp-server-kalshi": {
      "command": "uvx",
      "args": [
        "mcp-server-kalshi"
      ],
      "env": {
        "KALSHI_ENV": "YOUR_KALSHI_ENV_HERE",
        "KALSHI_API_KEY": "YOUR_KALSHI_API_KEY_HERE",
        "KALSHI_PRIVATE_KEY_PATH": "YOUR_KALSHI_PRIVATE_KEY_PATH_HERE",
        "BASE_URL": "YOUR_BASE_URL_HERE"
      }
    }
  }
}

{
  "mcpServers": {
    "modelrunner": {
      "url": "https://mcp.modelrunner.run/mcp"
    }
  }
}

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