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Youtube Research MCP Server

@lee-s-dev

代码仓库

基本信息

分类

数据与分析

传输方式

stdio

作者

lee-s-dev

提交者

이상준

关于 Youtube Research MCP Server

YouTube MCP server — transcripts, comments & channel analysis as AI research source

Youtube Research 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": {
    "youtube-research": {
      "command": "uvx",
      "args": [
        "youtube-research-mcp"
      ]
    }
  }
}

Youtube Research 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 Youtube Research Mcp?

A server that integrates YouTube subtitles, comments, and channel data as research sources for AI assistants via the Model Context Protocol (MCP). It works with any MCP‑capable AI client (Claude Desktop, Cursor, Windsurf, Cline, etc.) and requires no API key for subtitle and channel analysis; an optional YouTube Data API key unlocks video search and comment analysis.

How to use Youtube Research Mcp?

Install it with uvx youtube-research-mcp (recommended, requires uv) or pip install youtube-research-mcp. Then configure your MCP client (e.g., Claude Desktop’s claude_desktop_config.json) with the command uvx and arguments ["youtube-research-mcp"]. To use all features, set the environment variable YOUTUBE_API_KEY. Restart the client after configuration.

Key features of Youtube Research Mcp

  • Fetch video subtitles without any API key.
  • Analyze multiple videos in parallel (subtitles + optionally comments).
  • Analyze a YouTube channel’s recent videos.
  • Search videos by keyword (requires API key).
  • Collect video comments and discussions (requires API key).
  • Cache results in local SQLite to avoid redundant API calls.
  • Prompt injection defense via a safety_notice field.
  • No external data transmission or LLM calls.

Use cases of Youtube Research Mcp

  • Summarize the key points of a single YouTube video.
  • Compare arguments, commonalities, and differences across multiple videos.
  • Analyze recent content trends of a specific YouTube channel.
  • Search for videos on a topic and collect their subtitles and comments for research.
  • Compare creator claims with real audience reactions (comments).

常见问题

1

Do I need a YouTube API key?

No, for fetching subtitles and channel metadata. A free API key is required only for video search and comment collection (daily quota of 10,000 units).

2

Is it safe to install and use?

Yes. The server only fetches data from YouTube and caches it locally. It never sends collected data to external servers, never calls any LLM or AI API, never accesses files outside its cache directory, and never executes shell commands. Source code is public on GitHub.

3

What data is cached and for how long?

Subtitles are cached for 30 days, comments for 6 hours, search results for 2 hours, and video metadata permanently. Caching reduces duplicate API calls.

4

Where is the cache stored?

Default locations: macOS `~/Library/Application Support/youtube-research-mcp/cache.db`, Windows `%APPDATA%\youtube-research-mcp\cache.db`, Linux `~/.local/share/youtube-research-mcp/cache.db`. Override with the `YOUTUBE_RESEARCH_CACHE_DB` environment variable.

5

How do I install Youtube Research Mcp?

Use `uvx youtube-research-mcp` (recommended, requires `uv`) or `pip install youtube-research-mcp`. For pip installations, set the MCP client’s command to `"youtube-research-mcp"` with empty `args`.

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