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FILM FINDER Server

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A simple MCP server for fetching movie and TV show data from TMDB and OMDB APIs. Provides natural language capability for users to search, compare, and analyze

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Описание

A simple MCP server for fetching movie and TV show data from TMDB and OMDB APIs. Provides natural language capability for users to search, compare, and analyze movies through AI assistants.

README

A simple MCP (Model Context Protocol) server for fetching movie and TV show data from TMDB and OMDB APIs. Provides natural language capability for users to search, compare, and analyze movies through AI assistants.

What is Model Context Protocol?

MCP allows AI assistants (like Claude in Cursor) to access external tools and data sources. This server exposes movie databases as MCP tools.

What it does

  • Get popular movies and TV shows
  • Search movie details by ID or title
  • Compare ratings across TMDB and OMDB
  • Basic caching for faster responses

Setup

  1. Get API keys:

  2. Add keys to .cursor/mcp.json:

{
  "mcpServers": {
    "film-finder": {
      "command": "uv",
      "args": ["run", "--directory", "/path/to/film-finder-mcp/tmdb-mcp", "python", "src/server.py"],
      "env": {
        "TMDB_API_KEY": "your_tmdb_key",
        "OMDB_API_KEY": "your_omdb_key"
      }
    }
  }
}
  1. Install dependencies:
uv sync

Testing

Use MCP Inspector for testing:

npx @modelcontextprotocol/inspector uv run python src/server.py

Then open http://localhost:5173 (or the URL shown in terminal).

What is MCP Inspector?
A web-based developer tool for testing MCP servers during development. You can call tools, test prompts, and view resources without needing a full AI assistant setup.

Available Tools

Movies:

  • get_popular_movies - Popular movies by language/page
  • get_top_rated_movies - Highest rated movies
  • get_movie_details - TMDB details by movie ID
  • get_movie_details_by_title - OMDB search by title
  • get_movie_recommendation - Discover movies by genre/language

TV Shows:

  • get_popular_tv_shows - Popular TV shows
  • get_top_rated_tv_shows - Highest rated shows
  • get_tv_show_details - Details for specific show

Other:

  • authenticate_api_key - Validate TMDB API key
  • generate_recommendation_explanation - AI-powered movie recommendations

Prompts

Pre-configured prompts to guide AI responses:

  • movie_recommendation_prompt - Guide for recommending movies
  • tv_show_recommendation_prompt - Guide for TV show suggestions
  • movie_analysis_prompt - Compare and analyze movies
  • compare_movie_sources_prompt - Compare TMDB vs OMDB data

Resources

Static and dynamic data exposed by the server:

  • tmdb://config - TMDB API configuration (languages, genres)
  • omdb://config - OMDB API configuration
  • tmdb://movie/{movie_id} - Dynamic movie details by ID
  • tmdb://movie/top_rated - Top rated movies list

Use MCP Inspector's Resources tab to explore these.

Caching

Results are cached using Python's cachetools with TTL (Time To Live):

Data Type Cache Duration Reason
Popular movies/shows 3 hours Changes daily
Movie details 24 hours Static metadata
Top rated 6 hours Rarely changes

Example Usage in Cursor

Once configured in .cursor/mcp.json, ask Claude or any other LLM:

  • "What are the top rated movies right now?"
  • "Compare The Godfather ratings on TMDB vs OMDB"
  • "Recommend me some movies similar to Inception"

The AI will automatically use your MCP tools to fetch and analyze movie data.

Here is an example

Troubleshooting

Server won't start:

  • Check that API keys are set in .cursor/mcp.json
  • Verify uv sync ran successfully
  • Look for errors in terminal logs
  • Run from terminal uv run python src/server.py and check for logging.

Project Structure

film-finder-mcp/
├── src/
│   ├── server.py           # Main MCP server
│   └── tools/
│       ├── tmdb_client.py  # TMDB API client with caching
│       ├── omdb_client.py  # OMDB API client
│       └── base_config.py  # Configuration and logging
├── test_my_http_client.py  # Test file
├── pyproject.toml           # Dependencies
├── images/                  # Screenshots
└── README.md                # You are here

Notes

This is a learning project to understand MCP server development. The code works but could be improved with better error handling, more comprehensive tests, and additional features!

from github.com/rajatk10/film-finder-mcp

Установка FILM FINDER Server

У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.

▸ github.com/rajatk10/film-finder-mcp

FAQ

FILM FINDER Server MCP бесплатный?

Да, FILM FINDER Server MCP бесплатный — установка в пару кликов через Unyly без оплаты.

Нужен ли API-ключ для FILM FINDER Server?

Нет, FILM FINDER Server работает без API-ключей и переменных окружения.

FILM FINDER Server — hosted или self-hosted?

Доступен hosted-вариант: Unyly запускает сервер в облаке, локальная установка не обязательна.

Как установить FILM FINDER Server в Claude Desktop, Claude Code или Cursor?

Открой FILM FINDER Server на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.

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