MCP Server

Connect AI agents to Codegen using the Model Context Protocol (MCP) server

The Codegen MCP server enables AI agents to interact with the Codegen platform through the Model Context Protocol (MCP). This integration allows AI agents to access Codegen APIs, manage agent runs, and interact with your development workflow.

Overview

The MCP server provides:

• API Integration: Direct access to Codegen platform APIs
• Agent Management: Create and monitor agent runs
• Organization Management: Access organization and user information
• Workflow Integration: Seamless integration with AI development tools

Installation

The MCP server is included with the Codegen CLI. Install it using:

uv tool install codegen

Configuration

For Cline (VS Code Extension)

Add this to your cline_mcp_settings.json file:

{
  "mcpServers": {
    "codegen": {
      "command": "codegen",
      "args": ["mcp"],
      "cwd": "<path to your project>"
    }
  }
}

For Claude Desktop

Under the Settings > Feature > MCP Servers section, click “Add New MCP Server” and add the following:

• Server Name: codegen-mcp
• Command: codegen
• Arguments: ["mcp"]

Usage

Starting the Server

Start the MCP server using the Codegen CLI:

# Start with stdio transport (default)
codegen mcp

# Start with HTTP transport on a specific port
codegen mcp --transport http --port 8080

# Start with custom host and port
codegen mcp --transport http --host 0.0.0.0 --port 3000

The server will display the transport method and port information when it starts:

🚀 Starting Codegen MCP server...
📡 Using stdio transport
🚀 MCP server running on stdio transport

Environment Variables

Configure the MCP server using these environment variables:

• CODEGEN_API_KEY: Your Codegen API key for authentication
• CODEGEN_API_BASE_URL: Base URL for the Codegen API (defaults to https://api.codegen.com)

Available Tools

The MCP server provides the following tools for AI agents:

Agent Management

• create_agent_run: Create a new agent run in your organization
• get_agent_run: Get details of a specific agent run

Organization Management

• get_organizations: List organizations you have access to
• get_users: List users in an organization
• get_user: Get details of a specific user

Transport Options

The MCP server supports two transport methods:

stdio (Default)

• Best for most AI agents and IDE integrations
• Direct communication through standard input/output
• No network configuration required

HTTP

• Useful for web-based integrations
• Requires specifying host and port
• Currently falls back to stdio (HTTP support coming soon)

Authentication

The MCP server uses your Codegen API key for authentication. You can obtain your API key from the Codegen dashboard.

Set your API key as an environment variable:

export CODEGEN_API_KEY="your-api-key-here"

Troubleshooting

Common Issues

Server won’t start

• Ensure the Codegen CLI is properly installed
• Check that your API key is set correctly
• Verify network connectivity to the Codegen API

Authentication errors

• Verify your API key is valid and not expired
• Check that the API key has the necessary permissions
• Ensure the CODEGEN_API_KEY environment variable is set

Connection issues

• For stdio transport, ensure your AI agent supports MCP
• For HTTP transport, check firewall settings and port availability
• Verify the host and port configuration

Getting Help

If you encounter issues with the MCP server:

1. Check the Codegen documentation
2. Join our community Slack
3. Report issues on GitHub

Examples

Creating an Agent Run

# Example of how an AI agent might use the MCP server
# This would be handled automatically by your AI agent

{
  "tool": "create_agent_run",
  "arguments": {
    "org_id": 123,
    "prompt": "Review the latest pull request and suggest improvements",
    "repo_name": "my-project",
    "branch_name": "feature-branch"
  }
}

Getting Organization Information

{
  "tool": "get_organizations",
  "arguments": {
    "page": 1,
    "limit": 10
  }
}

The MCP server makes it easy to integrate Codegen’s powerful AI development capabilities into your existing AI agent workflows.