YouTube Research MCP Server

YouTube Research MCP MCP server is a locally run integration for AI assistants that speak the Model Context Protocol. Citation-ready YouTube transcript research and optional channel intelligence for AI agents.

What you get

Turn YouTube videos into citation-ready research for Codex, Claude, Cursor, and other MCP clients. Paste a video URL and get transcript evidence with timestamps and links that open at the exact quoted moment.

• Citation-ready research — — every transcript segment includes a timestamp and source URL
• Zero-key quick start — — transcripts work immediately; add an API key only for search and analytics
• URL-first input — — accepts normal, short, Shorts, embed, live, and raw video-ID formats
• Agent-efficient filtering — — search inside transcripts and return nearby context instead of spending tokens on the entire video
• Full YouTube intelligence — — optional API mode adds comments, video/channel statistics, trends, and comparisons
• Remote-native MCP — — Streamable HTTP transport at /mcp, plus Docker and Smithery support

What the assistant can call

Once YouTube Research MCP is connected, these are the calls the assistant has available:

• research-video — Get citation-ready transcript evidence from a URL or video ID without an API key
• research-videos — Compare timestamp-linked evidence across 2–5 videos without an API key
• search-videos — Search for YouTube videos with advanced filtering options
• get-video-comments — Get comments for a specific video
• get-video-transcript — Get transcript for a specific video with optional language
• enhanced-transcript — Advanced transcript extraction with filtering, search, and multi-video capabilities
• get-key-moments — Extract key moments with timestamps from a video transcript for easier navigation
• get-segmented-transcript — Divide a video transcript into segments for easier analysis
• get-video-stats — Get statistical information for a specific video
• get-channel-stats — Get subscriber count, view count, and other channel statistics
• compare-videos — Compare statistics across multiple videos
• get-trending-videos — Retrieve trending videos by region and category

Configuration and credentials

You will need 7 environment variables: YOUTUBE_API_KEY, MCP_BEARER_TOKEN, CORS_ORIGIN, MAX_SESSIONS, SESSION_IDLE_TIMEOUT_MS, YOUTUBE_MCP_TOKEN, VIDEO_ID. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.

Setting it up

Installation goes through your MCP client rather than a global install: point it at @coyasong/youtube-mcp-server on npm and it is fetched when the client starts. The copy-paste blocks for Claude Desktop, Claude Code and Cursor are further down this page.

Choosing this one

This sits in the cloud and infrastructure group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. YouTube Research MCP's toolset — research-video, research-videos, search-videos and 11 more — is a fair guide to whether it matches your workflow. It is maintained by coyaSONG; worth a glance at recent repository activity before you build anything load-bearing on it.

This entry was verified against YouTube Research MCP's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.

Before you rely on it

• It runs with your machine's permissions. That is convenient and also the reason to think about what you point it at before you approve a tool call.
• With 14 tools registered it takes up a noticeable share of the context window; turn it off in projects that never touch YouTube Research MCP.
• Missing credentials fail quietly in some clients — if no tools show up, check the environment block first.
• MCP clients confirm each tool call by default. Leave that on until you have watched what the youtube research mcp mcp server does with a few real requests.