Mandoline MCP Server

🚀 Mandoline MCP Server

Enable AI assistants such as Claude Code, Claude Desktop, and Cursor to reflect on, critique, and continuously enhance their own performance using Mandoline's evaluation framework via the Model Context Protocol.

🚀 Quick Start

Client Setup

Most users should start here. Integrate evaluation tools into your AI assistant by using Mandoline's hosted MCP server.

For each integration below, replace sk_**** with your actual API key from mandoline.ai/account.

Claude Code

Use the CLI to add the Mandoline MCP server to Claude Code:

claude mcp add --scope user --transport http mandoline https://mandoline.ai/mcp --header "x-api-key: sk_****"

You can use --scope user (across projects) or --scope project (current project only).

⚠️ Important Note

Restart any active Claude Code sessions after configuration changes.

💡 Usage Tip

Run /mcp in Claude Code to see Mandoline listed as an active server.

Official Documentation: Claude Code MCP Guide

Claude Desktop

Edit your configuration file (Settings > Developer > Edit Config):

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "Mandoline": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://mandoline.ai/mcp",
        "--header",
        "x-api-key: ${MANDOLINE_API_KEY}"
      ],
      "env": {
        "MANDOLINE_API_KEY": "sk_****"
      }
    }
  }
}

This configuration applies globally to all conversations.

⚠️ Important Note

Restart Claude Desktop after configuration changes.

💡 Usage Tip

Look for Mandoline tools when you click the "Search and tools" button.

Official Documentation: MCP Quickstart Guide

Cursor

Create or edit your MCP configuration file:

{
  "mcpServers": {
    "Mandoline": {
      "url": "https://mandoline.ai/mcp",
      "headers": {
        "x-api-key": "sk_****"
      }
    }
  }
}

You can use your global configuration (affects all projects) ~/.cursor/mcp.json or project-local configuration (current project only) .cursor/mcp.json (in project root)

⚠️ Important Note

Restart Cursor after configuration changes.

💡 Usage Tip

Check the Output panel (Ctrl+Shift+U) → "MCP Logs" for successful connection, or look for Mandoline tools in the Composer Agent.

Official Documentation: Cursor MCP Guide

Server Setup

Only needed if you want to run the server locally or contribute to development. Most users should use the hosted server above.

Prerequisites: Node.js 18+ and npm

Installation

1. Clone and build

   git clone https://github.com/mandoline-ai/mandoline-mcp-server.git
   cd mandoline-mcp-server
   npm install
   npm run build
   

2. Configure environment (optional)

   cp .env.example .env.local
   # Edit .env.local to customize PORT, LOG_LEVEL, etc.
   

3. Start the server

   npm start
   

The server runs on http://localhost:8080 by default.

Using Local Server

To use your local server instead of the hosted one, replace https://mandoline.ai/mcp with http://localhost:8080/mcp in the client configurations above.

💻 Usage Examples

Basic Usage

Once integrated, you can use Mandoline evaluation tools directly in your AI assistant conversations.

Tools

Metrics

Evaluations

Resources

Access Mandoline's documentation and reference materials directly in your AI assistant, including model comparison guides and evaluation best practices.

📚 Documentation

Support

• Platform: https://mandoline.ai - Create account and get API keys
• Documentation: https://mandoline.ai/docs - Evaluation guides and best practices
• Issues: GitHub Issues - Bug reports and feature requests
• Email: support@mandoline.ai - Direct support

License

Apache-2.0 License - see the LICENSE file for details.