YouTube Knowledge MCP
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| LOG_LEVEL | No | Log level for the application | info |
| REDIS_URL | No | Redis connection URL (e.g. redis://localhost:6379) | |
| REDIS_HOST | No | Redis host | |
| REDIS_PORT | No | Redis port | |
| OPENAI_API_KEY | No | Optional OpenAI API key for AI tools (enables analyze_video_content, generate_learning_path, analyze_comment_intents, simplify_video_transcript, generate_video_chapters, generate_knowledge_graph) | |
| REDIS_PASSWORD | No | Redis password | |
| MAX_DAILY_QUOTA | No | Maximum daily quota for YouTube API usage | 8000 |
| YOUTUBE_API_KEY | Yes | Your YouTube Data API v3 key | |
| ANTHROPIC_API_KEY | No | Optional Anthropic API key for AI tools (enables analyze_video_content, generate_learning_path, analyze_comment_intents, simplify_video_transcript, generate_video_chapters, generate_knowledge_graph) |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| youtube_searchC | Search for videos on YouTube with advanced filtering options |
| get_video_detailsB | Get comprehensive information about a specific YouTube video |
| get_trending_videosC | Discover trending videos in different categories and regions |
| analyze_video_contentC | Get AI-powered analysis and insights from video content |
| search_channelsC | Find and analyze YouTube channels |
| generate_learning_pathC | Generate AI-powered learning paths from YouTube content with difficulty assessment |
| analyze_comment_intentsC | Analyze YouTube comments to extract user intents and actionable insights |
| simplify_video_transcriptB | Create age-appropriate simplified versions of video transcripts (ELI5 mode) |
| generate_video_chaptersB | Generate AI-powered video chapters with timestamps and descriptions |
| generate_knowledge_graphC | Create cross-video knowledge graphs showing concept relationships |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 10 tools
Each tool has a clearly distinct purpose targeting specific YouTube operations: content analysis, search, metadata retrieval, and content transformation. There is no overlap in functionality; for example, analyze_video_content focuses on video insights while simplify_video_transcript handles transcript simplification, making misselection unlikely.
The naming follows a consistent verb_noun pattern with snake_case throughout, such as analyze_comment_intents and generate_video_chapters. The only minor deviation is youtube_search, which uses the platform name as a prefix instead of a verb, but it still fits the overall readable convention.
With 10 tools, the count is well-scoped for a YouTube knowledge server, covering a broad range of functionalities from search and analysis to content generation. Each tool earns its place by addressing distinct aspects of video and channel processing without feeling excessive or insufficient.
The tool set provides comprehensive coverage for YouTube knowledge extraction, including search, analysis, metadata retrieval, and content transformation. Minor gaps exist, such as the lack of tools for managing playlists or user interactions, but core workflows for learning and insights are well-supported.