oratilo-mcp
Related Servers
Alternatives to oratilo-mcp
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityDmaintenanceProvides tools for searching YouTube videos, retrieving transcripts, and performing semantic search over video content.MIT
- AlicenseCqualityBmaintenanceEnables AI agents to search, analyze, and extract insights from YouTube videos including transcripts, visual frames, and benchmarks without requiring API keys. Supports semantic search across playlists, sentiment analysis, and visual content indexing with automatic fallback chains for reliable access.4151 npm35MIT
- FlicenseNot gradedqualityDmaintenanceEnables LLMs to interact with YouTube videos by fetching transcripts, summarizing content, and answering questions based on video context.-
- AlicenseBqualityDmaintenanceEnables AI assistants to search YouTube videos using the official YouTube Data API v3, extract full video transcripts in multiple languages, and store/retrieve video summaries using a local database.4MIT
- FlicenseAqualityCmaintenanceEnables AI agents to fetch, search, and summarize YouTube video transcripts via tools, resources, and prompts.3-
- AlicenseBqualityCmaintenanceEnables extraction of transcripts, keyword-based video search with metadata retrieval, and channel information discovery from YouTube videos through natural language interaction.34MIT
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: lookup is for checking a specific video ID/URL for existing coverage, while search is for discovering what content exists by topic when no specific URL is known. The descriptions explicitly clarify when to use each, leaving no ambiguity whatsoever.
Both tools follow a consistent oratilo_ prefix with a clear verb (lookup, search). The pattern is consistent and predictable, though with only two tools the naming convention is minimally demonstrated.
At 2 tools, the surface feels thin for a library with search and retrieval capabilities, though it could be argued these two operations are the core of what's needed. The count is borderline but reasonable given the limited scope described.
Core read operations (lookup and search) are covered, providing a functional surface. However, there are no write/contribution tools (e.g., adding or updating a summary), so the surface covers only the lookup half of the workflow and leaves the 'summarize it yourself' path entirely to the agent.