omdb-mcp-server
by tyrell·★ 1·Score 34
A Java-based MCP server for OMDB API that enables AI assistants to search for movies and retrieve detailed movie information.
Overview
The OMDB MCP Server is a production-ready implementation built with Spring Boot and Spring AI, providing access to the Open Movie Database through MCP protocol. It features intelligent caching, comprehensive tool coverage, and modern architecture with reactive programming. The server implements MCP 2024-11-05 specification with HTTP JSON-RPC transport, offering tools for movie search, detail retrieval, and movie lookup by IMDB ID.
Try asking AI
After installing, here are 5 things you can ask your AI assistant:
When to choose this
Choose this server when you need movie data integration for AI assistants and want the performance benefits of intelligent caching.
When NOT to choose this
Don't choose this if you need real-time movie data (cache has 1-hour TTL) or want a language other than Java implementation.
Tools this server exposes
3 tools extracted from the READMEsearch_moviesSearch for movies by title in the OMDB database
get_movie_detailsRetrieve detailed information about a specific movie by title
get_movie_by_imdb_idGet detailed information about a movie using its IMDB ID
Comparable tools
Installation
Installation
**Docker (Recommended)**
docker run -p 8081:8081 -e OMDB_API_KEY=your-api-key ghcr.io/tyrell/omdb-mcp-server:latest**Pre-built JAR**
java -jar omdb-mcp-server-*.jar --omdb.api.key=your-api-key**Building from Source**
git clone https://github.com/tyrell/omdb-mcp-server
cd omdb-mcp-server
./mvnw clean package
export OMDB_API_KEY=your-api-key
./mvnw spring-boot:run**Claude Desktop Configuration** Add to your Claude Desktop config.json:
{
"mcpServers": {
"omdb": {
"command": "docker",
"args": ["run", "--rm", "-p", "8081:8081", "-e", "OMDB_API_KEY=your-api-key", "ghcr.io/tyrell/omdb-mcp-server:latest"]
}
}
}FAQ
- What OMDB API tools are available?
- The server provides three main tools: search_movies (search by title/year/type), get_movie_details (retrieve details by title), and get_movie_by_imdb_id (get details using IMDB ID).
- How is caching implemented?
- The server uses Caffeine in-memory caching with a default TTL of 1 hour and a maximum of 1000 entries with LRU eviction policy. Cache statistics can be accessed via /cache/stats endpoint.
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Last updated · Auto-generated from public README + GitHub signals.