About YouTube MCP Server
YouTube MCP Server is an MCP server for searching YouTube videos, retrieving transcripts, and running semantic search over stored video content. It does not rely on the official YouTube API, making it suited to users who want LLM-driven access to video material.
Key features
- 01Searches YouTube videos without the official API
- 02Retrieves video transcripts
- 03Stores video information and transcripts in a vector database
- 04Semantic search over stored transcripts
Use cases
- 01Finding tutorial videos on a topic from a chat
- 02Extracting transcripts for summaries or question answering
- 03Searching stored videos for content on topics such as machine learning
MCP support
The project is an MCP server that exposes four tools to MCP clients: search-youtube, get-transcript, store-video-info, and search-transcripts.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEYouTube MCP Server
A Model Context Protocol (MCP) server that provides tools for searching YouTube videos, retrieving transcripts, and performing semantic search over video content.
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Table of Contents
- YouTube MCP Server
- Features
- Prerequisites
- Installation
- Running the Server
- Available Tools
- Using with MCP Clients
- Debugging
- Contributing
- License
Features
- Search YouTube videos without using the official API
- Retrieve video transcripts
- Store video information and transcripts in a vector database
- Perform semantic search over stored video transcripts
Prerequisites
- Python 3.8+
- Google API key for embeddings
- uv package manager
Installation
-
Clone this repository
-
Create and activate a virtual environment using uv:
uv venv
# On Windows:
.venv\Scripts\activate
# On Unix/MacOS:
source .venv/bin/activate
- Install dependencies using uv:
uv pip install -r requirements.txt
- Create a
.envfile with your Google API key:
GOOGLE_API_KEY=your_api_key_here
Running the Server
There are two ways to run the MCP server:
1. Direct Method
To start the MCP server directly:
uv run python server.py
2. Configure for Claude.app
Add to your Claude settings without using any package manager this works for windows:
"mcpServers": {
"youtube": {
"command": "C:\\Path\\To\\Your\\Project\\.venv\\Scripts\\python.exe",
"args": ["C:\\Path\\To\\Your\\Project\\server.py"],
"env": {
"GOOGLE_API_KEY": "your_api_key_here"
}
}
}
Using Uv package manager this works for windows:
"mcpServers": {
"youtube": {
"command": "uv",
"args": ["--directory", "C:\\Path\\To\\Your\\Project", "run", "server.py"],
"env": {
"GOOGLE_API_KEY": "your_api_key_here"
}
}
}
Available Tools
The server provides the following tools:
-
search-youtube: Search for YouTube videos based on a query- Parameters:
- query: Search query string
- max_results: Maximum number of results to return (default: 5)
- Parameters:
-
get-transcript: Get the transcript of a YouTube video- Parameters:
- video_url: URL of the YouTube video
- Parameters:
-
store-video-info: Store video information and transcript in the vector database- Parameters:
- video_url: URL of the YouTube video
- metadata: Optional metadata about the video
- Parameters:
-
search-transcripts: Search stored video transcripts using semantic search- Parameters:
- query: Search query
- limit: Maximum number of results to return (default: 3)
- Parameters:
Using with MCP Clients
This server can be used with any MCP-compatible client, such as Claude Desktop App. The tools will be automatically discovered and made available to the client.
Example Usage
- Start the server using one of the methods described above
- Open Claude Desktop App
- Look for the hammer icon to verify that the YouTube tools are available
- You can now use commands like:
- "Search for Python tutorial videos"
- "Get the transcript of this video: [video_url]"
- "Search through stored video transcripts about machine learning"
Debugging
If you encounter any issues:
- Make sure your Google API key is correctly set in the
.envfile - Check that all dependencies are installed correctly
- Verify that the server is running and listening for connections
- Look for any error messages in the server output
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
License
This project is licensed under the MIT License - see the LICENSE file for details.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.