What do I need to use IMDb MCP Server?
Python 3.13 or higher, a RapidAPI account with a subscription to the IMDb API, and either `uv` (recommended) or `pip` for dependency management.
IMDb MCP Server
@uzaysozen
基本信息
关于 IMDb MCP Server
暂无概览
#imdb#movie-api#tv-show-api
IMDb MCP Server 配置
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"imdb-mcp-server": {
"command": "npx",
"args": [
"-y",
"@smithery/cli",
"install",
"@uzaysozen/imdb-mcp-server",
"--client",
"claude"
]
}
}
}IMDb MCP Server 工具
工具列表暂未提供
当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。
点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。
概览
What is IMDb MCP Server?
A Python server implementing the Model Context Protocol (MCP) that provides movie and TV show information using the IMDb API via RapidAPI. It serves as a bridge between AI agents and the IMDb database, offering tools to search, retrieve details, and browse lists of content.
How to use IMDb MCP Server?
Install via Smithery (recommended), Docker, or direct Python execution with uv. Configure the required RapidAPI key either as an environment variable (RAPID_API_KEY_IMDB) or through Smithery’s per-request system. The server supports two transport modes: stdio (default for local development) and HTTP (used by Docker and Smithery). Start with uv run imdb-server or TRANSPORT=http uv run imdb-server.
Key features of IMDb MCP Server
- Search movies and TV shows with filtering options
- Retrieve detailed information, cast, crew, directors, writers
- Access top 250 movies, top 250 TV shows, most popular lists
- Get US box office records and upcoming releases by country
- Special Indian cinema tools (Malayalam, Tamil, Telugu, Hindi)
- Efficient in-memory caching with LRU eviction
- Smart pagination (5 items per page) for AI-optimized responses
Use cases of IMDb MCP Server
- Find upcoming action movies and their release dates
- Get detailed information about a specific movie or TV show
- Explore top-rated or trending content in different genres and countries
- Discover Indian cinema with dedicated tools for regional film industries
常见问题
How does the server handle data limits for AI agents?
All collection endpoints implement pagination with a fixed page size of 5 items. Each paginated tool accepts a `start` parameter and returns navigation metadata (`totalCount`, `hasMore`, `nextStart`) to help AI agents process data in manageable chunks.
What transport modes are supported?
Stdio mode (default, for local Claude Desktop) and HTTP mode (for Docker and Smithery). HTTP mode runs on port 8081 by default and supports CORS.
Where does the data come from and is authentication required?
All data is fetched from the IMDb API hosted on RapidAPI. An API key is required, configured either as an environment variable (`RAPID_API_KEY_IMDB`) or via Smithery’s configuration system for per-request authentication.
Are there any known limitations?
The server requires an active RapidAPI subscription and internet access. Results are limited to 5 items per request for paginated endpoints. Caching is in-memory only and not persisted across server restarts.
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