Movies MCP Server

A production-ready Model Context Protocol (MCP) server for intelligent movie database management, built with Clean Architecture principles and optimized for AI-assisted environments.

🎉 Powered by Official Golang MCP SDK v1.1.0 Built with the official MCP SDK maintained by Anthropic and Google, providing type safety, automatic schema generation, and production-ready reliability. See SDK Migration for migration details.

✅ SDK-Only Implementation The legacy custom server has been archived. This project now uses only the official SDK-based server at cmd/server-sdk/. See Server Status for details.

What is Movies MCP Server?

Movies MCP Server is a sophisticated movie database management system that communicates via the Model Context Protocol—designed specifically for integration with AI assistants like Claude. Unlike traditional HTTP APIs, it uses JSON-RPC over stdin/stdout to provide seamless, intelligent movie and actor data operations.

Perfect for:

• AI-powered movie recommendation systems
• Claude Desktop integrations
• Intelligent film analysis and exploration
• Director career research
• Movie database management with AI assistance

Why Choose Movies MCP Server?

• MCP Protocol Native: Built specifically for the Model Context Protocol using the official Golang SDK
• Type-Safe & Modern: Leverages official SDK for compile-time validation and automatic schema generation
• Clean Architecture: Exemplary separation of concerns with domain-driven design
• Intelligent Features: AI-powered recommendations, director career analysis, and similarity searches
• Comprehensive Actor Management: Full actor database with movie associations and career tracking
• Production-Ready: Health checks, Prometheus metrics, Grafana dashboards, and comprehensive monitoring
• Advanced Search: Full-text search, decade filtering, rating ranges, genre matching, and similarity scoring
• Image Support: Store and retrieve movie posters via MCP resources with base64 encoding
• BDD Testing: Comprehensive test coverage with Cucumber/Godog behavior scenarios
• Docker-Optimized: Multi-stage builds, distroless images, non-root execution

Key Performance Metrics

• Throughput: >50 operations/second under load
• Concurrency: Safely handles 50+ concurrent requests
• Response Time: <100ms for typical operations
• Test Coverage: Comprehensive unit and integration tests with BDD scenarios
• Code Efficiency: 26% less code with SDK migration (eliminated ~1,200 lines)

MCP Capabilities

23 Available Tools

Movie Management (8 tools)

• get_movie - Retrieve movie by ID
• add_movie - Create movie with title, director, year, rating, genres, poster
• update_movie - Update existing movie details
• delete_movie - Delete movie by ID
• list_top_movies - Get top-rated movies with configurable limit
• search_movies - Multi-criteria search (title, director, genre, year range, rating)
• search_by_decade - Find movies from specific decades (1990s, 2000s, etc.)
• search_by_rating_range - Filter movies by rating boundaries

Actor Management (9 tools)

• add_actor - Create actor with name, birth year, biography
• get_actor - Retrieve actor by ID
• update_actor - Update actor information
• delete_actor - Delete actor
• link_actor_to_movie - Associate actor with movie
• unlink_actor_from_movie - Remove actor-movie association
• get_movie_cast - Get all actors in a movie
• get_actor_movies - Get all movies for an actor
• search_actors - Search actors by name with birth year filtering

Intelligence & Analysis (3 compound tools)

• bulk_movie_import - Import multiple movies with error tracking
• movie_recommendation_engine - AI-powered recommendations with preference scoring
• director_career_analysis - Career trajectory with early/mid/l

... View full README on GitHub