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MCP Media Server

@Bzcasper

代码仓库

基本信息

分类

媒体与设计

许可证

MIT license

传输方式

stdio

作者

Bzcasper

关于 MCP Media Server

暂无概览

#mcp-media-server#media-processing#ai-integration

MCP Media 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": {
    "mcp-media-server": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        "venv"
      ]
    }
  }
}

MCP Media 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。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is MCP Media Server?

MCP Media Server is a custom MCP server built with Python that enables AI assistants like Claude to interact with media files, perform video processing, and integrate with Supabase and Pinecone for data storage and vector search. It provides YouTube downloading, FFmpeg processing, and RESTful API endpoints for media workflows.

How to use MCP Media Server?

Install manually (Python 3.10+, FFmpeg, dependencies) or via Docker. Run with python main.py for stdio transport, python main.py --transport sse for SSE, or python main.py --api to enable the REST API. Optionally use --transport sse --api for both. For production, deploy with Docker Compose and configure a systemd service. Integrate with Claude Desktop by adding an MCP server entry in its settings JSON.

Key features of MCP Media Server

  • YouTube video downloading via yt-dlp
  • Video processing with FFmpeg
  • Supabase integration for metadata storage
  • Pinecone integration for vector search
  • MCP server for AI assistant (Claude) integration
  • RESTful API gateway for HTTP access
  • Webhook, batch processing, and caching support
  • User authentication and API key management

Use cases of MCP Media Server

  • Download YouTube videos and process them for analysis
  • Perform semantic video search using vector embeddings
  • Integrate media processing into AI assistant workflows (e.g., Claude)
  • Run automated media pipelines with scheduled tasks and webhooks
  • Deploy a production-grade media server with Docker and monitoring

常见问题

1

What are the prerequisites to run MCP Media Server?

Python 3.10+, FFmpeg, a Supabase account, a Pinecone account, and an OpenAI API key (for embeddings). Docker and Docker Compose are needed for containerized deployment.

2

How do I start the MCP server?

Run `python main.py` from the project root. For SSE transport use `python main.py --transport sse`. To enable the API server add `--api` or combine both with `--transport sse --api`.

3

How can I integrate MCP Media Server with Claude Desktop?

In Claude Desktop's settings, add a new MCP server with the command pointing to your Python executable and arguments pointing to `main.py`. The server uses stdio transport by default.

4

What transport modes are available?

Two transport modes are available: stdio (default, for direct Claude Desktop integration) and SSE (Server-Sent Events, for remote HTTP-based connections).

5

Where are downloaded and processed files stored?

Files are stored locally in the `downloads/`, `processed/`, `thumbnails/`, and `cache/` directories within the project folder. Logs go to `logs/`.

评论

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