Medium MCP Server provides a programmatic interface to query Medium content, extract meaningful insights, and perform context-aware analysis using MCP (Model Context Protocol). The server exposes tools to fetch articles, authors, and publication data, then parse and summarize content with AI-driven extraction. With the included MCP capabilities, you can build AI assistants that understand Medium’s content structure, extract entities, generate summaries, and answer questions grounded in Medium articles. To get started, configure your API credentials, run the server, and use the available MCP endpoints to issue queries and retrieve structured results for downstream applications.

Prerequisites:

• Node.js v16 or later
• npm or yarn
• Medium API credentials (API key/secret)

Installation steps:

1. Clone the repository git clone https://github.com/Dishant27/medium-mcp-server.git

2. Navigate to the project directory cd medium-mcp-server

3. Install dependencies npm install

   or

   yarn install

4. Configure environment variables

   • Create a .env file (or export variables in your shell) with: MEDIUM_API_KEY=your-medium-api-key MEDIUM_API_SECRET=your-medium-api-secret

5. Start the server npm start

   or if a start script is defined in package.json:

   npm run start

6. Verify the server is running by hitting the MCP endpoint (e.g., http://localhost:3000/health) and test a sample query via your client.

Notes:

• If you don’t see a start script, you can run the server entry point directly with Node, e.g., node server.js, depending on how the project is structured after install.

Tips and common issues:

• Ensure your Medium API credentials are valid and have the necessary permissions for content retrieval.
• If you encounter CORS or network issues during local development, verify your environment and firewall settings.
• If the server fails to start due to missing modules, re-run npm install to ensure all dependencies are installed.
• Check logs for specific MCP endpoint usage; the server should expose endpoints for querying articles, authors, and content extraction.
• For production deployments, consider securing API keys via environment management and updating env vars without committing them to source control.