Provides access to YouTube-Summarizer APIs, allowing AI applications to summarize YouTube video content programmatically.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Youtube-Summarizer MCP Serversummarize the latest video from Veritasium"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP Server
MCP Server is created on top of all the APIs from the Youtube-Summarizer. All APIs are exposed as tools in the MCP protocol and available for any AI application to integrate with.
Note: Currently MCP only supports local connections, so it doesn't support remote use of these tools.
Setup
Docker Setup
Build the Docker image:
Run the MCP server using Docker:
Using the Inspector
You can use the MCP Inspector to explore available tools and test them:
Usage with Claude Desktop
Add the following to your claude_desktop_config.json:
Now you can use the added mcp tools from server.py in claude desktop
MCP Client Sample (Without Claude Desktop)
Run the MCP client locally to try out the Social Toolkit using natural language:
Setup
Run
It will run both MCP server and client, connected to each other. The terminal will prompt for natural language queries from the user, which then will be translated into MCP tool calls to answer the user query.