
An MCP server to extract Youtube captions and summarize videos
概览
This project provides a Model Context Protocol (MCP) server that acts as a proxy to the VidCap YouTube API, allowing AI assistants to easily access YouTube video data and functionalities. It also serves as a boilerplate for building custom MCP servers. This server also proxies requests to the VidCap YouTube API, providing convenient access to YouTube video data and functionalities. You will need a VIDCAP_API_KEY set in your environment variables. Endpoints are available under the /api/v1/youtube/ path: - - Description: Get and save YouTube video information. - Query Parameters: - url (string, required): YouTube video URL. - cache (boolean, optional, default: true): Whether to cache video info. - - Description: Get available media formats for a YouTube video. - Query Parameters: - url (string, required): YouTube video URL. - - Description: Get video captions/transcript. - Query Parameters: - url (string, required): YouTube video URL.
README
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VidCap YouTube API - MCP Server
This project provides a Model Context Protocol (MCP) server that acts as a proxy to the VidCap YouTube API, allowing AI assistants to easily access YouTube video data and functionalities. It also serves as a boilerplate for building custom MCP servers.
Table of Contents
VidCap YouTube API
This server also proxies requests to the VidCap YouTube API, providing convenient access to YouTube video data and functionalities. You will need a VIDCAP_API_KEY set in your environment variables.
Endpoints are available under the /api/v1/youtube/ path:
- GET
/info- Description: Get and save YouTube video information.
- Query Parameters:
url(string, required): YouTube video URL.cache(boolean, optional, default: true): Whether to cache video info.
- GET
/media- Description: Get available media formats for a YouTube video.
- Query Parameters:
url(string, required): YouTube video URL.
- GET
/caption- Description: Get video captions/transcript.
- Query Parameters:
url(string, required): YouTube video URL.locale(string, optional, default: ‘en’): Language code for captions.model(string, optional): AI model for processing.ext(enum, optional): File extension for captions (json3, srv1, srv2, srv3, ttml, vtt).
- GET
/summary- Description: Get AI-generated summary of video content.
- Query Parameters:
url(string, required): YouTube video URL.locale(string, optional, default: ‘en’): Target language code for summary.model(string, optional): AI model for summarization.screenshot(string, optional, default: ‘0’): ‘1’ to enable auto-screenshots for summary parts.cache(boolean, optional): Whether to use cached results.
- GET
/screenshot- Description: Get screenshot from video at specific timestamp.
- Query Parameters:
url(string, required): YouTube video URL.second(string, optional, default: ‘0’): Timestamp in seconds or YouTube time format.
- GET
/screenshot-multiple- Description: Get multiple screenshots from video at different timestamps.
- Query Parameters:
url(string, required): YouTube video URL.
安装
npx vidcap-mcp-server配置
{
"mcpServers": {
"vidcap-youtube-api": {
"command": "npx",
"args": ["vidcap-mcp-server"],
"env": {
"VIDCAP_API_KEY": "your_api_key_here"
}
}
}
}