This MCP server provides a Python-based harness for integrating Harness with Model Context Protocol (MCP) workflows and GenAI applications. It exposes an MCP-compliant server that you can run locally or in your environment, enabling you to manage Harness API requests through the MCP interface and harnessed AI interactions. The server is designed to handle authentication, rate limiting, and error retry logic, making it suitable for production-like usage when integrating with GenAI tools and workflows.

To use the server, install the package, set up your Harness credentials and base URL, and start the MCP server. You can then connect MCP clients to the server to perform Harness operations, fetch data, and orchestrate tasks via the MCP payloads. The server exposes methods to initialize the Harness connection, issue API calls, and manage responses in a structured MCP format compatible with downstream GenAI tooling.

Prerequisites:

• Python 3.8 or newer
• pip (usually installed with Python)
• Access credentials for Harness API

Installation steps:

1. Create a virtual environment (recommended) python -m venv venv

   On Windows:

   venv\Scripts\activate

   On macOS/Linux:

   source venv/bin/activate

2. Install the MCP server package pip install harness-mcp-server

3. (Optional) Verify installation python -m harness_mcp --help

4. Set up environment variables (see notes): export HARNESS_API_KEY=<your_api_key> export HARNESS_API_BASE_URL=https://api.harness.example

5. Run the MCP server (as described in mcp_config) python -m harness_mcp

Environment variables:

• HARNESS_API_KEY: Your Harness authentication key.
• HARNESS_API_BASE_URL: Base URL for Harness API endpoints.

Configuration tips:

• Ensure network access to the Harness API endpoints from the host running the MCP server.
• Use a .env file or your deployment environment's secret management to store API keys securely.
• If you need to customize behavior (timeouts, retry policies), update the server configuration or environment accordingly.

Common issues:

• Invalid API key or base URL results in authentication errors; verify credentials and endpoints.
• Firewall or network restrictions blocking API calls; ensure outbound access to Harness endpoints.
• Dependency/version misalignment; prefer using a virtual environment and the latest harness-mcp-server release.