The official Model Context Protocol server for Coval - the AI evaluation platform.

This MCP server allows AI assistants like Claude Desktop and Cursor to interact with Coval's evaluation APIs, enabling you to:

• Launch and monitor evaluation runs
• Manage AI agents and test sets
• Retrieve evaluation metrics and results

npx @covalai/mcp-server

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "coval": {
      "command": "npx",
      "args": ["-y", "@covalai/mcp-server"],
      "env": {
        "COVAL_API_KEY": "your_api_key_here"
      }
    }
  }
}

Add to .cursor/mcp.json in your project:

{
  "mcpServers": {
    "coval": {
      "command": "npx",
      "args": ["-y", "@covalai/mcp-server"],
      "env": {
        "COVAL_API_KEY": "your_api_key_here"
      }
    }
  }
}

{
  "mcpServers": {
    "coval": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://mcp.coval.dev/mcp",
        "--header",
        "X-API-KEY: ${COVAL_API_KEY}"
      ],
      "env": {
        "COVAL_API_KEY": "your_api_key_here"
      }
    }
  }
}

Get your API key from app.coval.dev/settings

Once connected, you can ask Claude things like:

"Show me my recent evaluation runs"

"List all my agents"

"Run an evaluation of my customer-support-agent against the billing-inquiries test set"

"What are the metrics for run abc123?"

# Install dependencies
npm install

# Build
npm run build

# Test locally with MCP Inspector
npm run inspector

# Run tests
npm test

• Coval Documentation
• MCP Protocol
• API Reference

MIT

• GitHub Issues
• Coval Support