Generic MCP Server
@csainath0210
About Generic MCP Server
A sample Model Context Protocol (MCP) server for movie database interactions. Built with TypeScript, Express, and the MCP SDK, it enables AI agents to search and discover films, actors, and directors through standardized tools and resources.
Config
No standard config provided
This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.
RepositoryTools
2Search for actors, directors, and film professionals with detailed information about their careers, biographical data, and filmographies.
Advanced film discovery with filtering by cast, genres, release dates, ratings, and more.
Overview
What is Generic MCP Server?
A production-ready Model Context Protocol (MCP) server built with TypeScript and Express, designed to seamlessly connect AI agents with external APIs. It provides developers with a practical reference for exposing APIs to AI agents and Large Language Models (LLMs), with a focus on movie database interactions using The Movie Database (TMDB).
How to use Generic MCP Server?
Clone the repository, install dependencies, configure a .env file with your TMDB access token and port (default 8089), then run in development mode (npm run dev) or production mode (npm run build && npm start). The server exposes an SSE endpoint at /sse and a message endpoint at /messages. An example client (npm run client) demonstrates connection and usage.
Key features of Generic MCP Server
- Full implementation of the MCP specification
- Real-time communication via Server-Sent Events (SSE)
- Modular architecture for easy extension
- Built-in movie database integration for searching and discovery
- Type-safe interfaces for API responses
- Comprehensive error handling
- Example client for testing and reference
Use cases of Generic MCP Server
- Search for actors, directors, and film professionals with detailed career information
- Discover films with advanced filtering (cast, genres, release dates, ratings, etc.)
- Integrate any MCP-compatible LLM with movie database capabilities
- Serve as a reference for building SSE-based MCP servers
FAQ from Generic MCP Server
What is MCP?
The Model Context Protocol (MCP) establishes a standardized interface for AI models to interact with external systems securely and efficiently, defining structures for resources, tools, and prompts.
What are the prerequisites for running Generic MCP Server?
Node.js 18 or higher and a package manager (npm or yarn). You also need a TMDB access token for the movie database features.
What environment variables are required?
PORT (default 8089) and ACCESS_TOKEN (your TMDB API access token) are required. Copy .env.example to .env and fill them in.
What endpoints does the server expose?
A GET endpoint at /sse for Server-Sent Events communication and a POST endpoint at /messages for clients to send messages to the MCP server.
Can I use this server with any AI model?
Yes, any LLM that supports the MCP protocol can integrate with this server. The standardized interface ensures compatibility across various AI frameworks and platforms.
Frequently asked questions
What is MCP?
The Model Context Protocol (MCP) establishes a standardized interface for AI models to interact with external systems securely and efficiently, defining structures for resources, tools, and prompts.
What are the prerequisites for running Generic MCP Server?
Node.js 18 or higher and a package manager (npm or yarn). You also need a TMDB access token for the movie database features.
What environment variables are required?
`PORT` (default `8089`) and `ACCESS_TOKEN` (your TMDB API access token) are required. Copy `.env.example` to `.env` and fill them in.
What endpoints does the server expose?
A GET endpoint at `/sse` for Server-Sent Events communication and a POST endpoint at `/messages` for clients to send messages to the MCP server.
Can I use this server with any AI model?
Yes, any LLM that supports the MCP protocol can integrate with this server. The standardized interface ensures compatibility across various AI frameworks and platforms.
Basic information
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