A lightweight Model Context Protocol (MCP) server for managing movie/TV series watchlists using TMDB data. Built with FastAPI, raw SQL, and Pydantic.
- Search, discover, and fetch movie/TV metadata via TMDB API
- Track watchlist items with statuses:
PlanToWatch,Watching,Watched,Dropped,OnHold - Store film info, metadata, and genres in SQLite using raw SQL
- JSON-RPC-style MCP interface over HTTP for structured command handling
- Python, FastAPI, Pydantic
- SQLite
- TMDB API
git clone https://github.com/yourusername/mcp-server.git
cd mcp-server
pip install -r requirements.txt
export TMDB_API_KEY=your_tmdb_key_here
uvicorn main:app --reloadNOTE: Create '.env' and add TMDB_API_KEY variable there
- UV (Recommended) Note: Install and configure (uv)[https://docs.astral.sh/uv/guides/tools/] for mcp before excuting
{
"mcpServers": {
"Movie MCP": {
"command": "uv",
"args": [
"run",
"mcp", "run", "[path_to_mcp_tmdb]/mcp_server.py"
]
}
}
}- Hacky way
{
"mcpServers": {
"Movie MCP": {
"command": "[path_to_mcp_tmdb]/setup.sh",
"args": []
}
}
}Use any Claude mcp config client and add above config. Use Console-chat-gpt CLI based chat MCP Client
Alternatively use (mcptools)[https://github.com/f/mcptools/]
- List tools
cd [path_to_movie_mcp]
mcptools tools uv run mcp run mcp_server.py- Search Movie
cd [path_to_movie_mcp]
mcptools call search_tmdb --params '{"query":"final destination", "type":"movie"}' uv run mcp run mcp_server.py