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lildaddyo/braintube-mcp

by Various

[](https://glama.ai/mcp/servers/lildaddyo/braintube-mcp) πŸ“‡ ☁️ - Compiles saved YouTube videos, podcasts, articles, PDFs, and Notion/Obsidian notes into a persistent, semantically

L

MCP

lildaddyo/braintube-mcp

Added 13 July 2026

Overview

Braintube-mcp compiles saved YouTube videos, podcasts, articles, PDFs, and notes from Notion or Obsidian into a persistent, semantically organized knowledge base. It runs as an MCP server built in TypeScript, enabling AI agents to query and retrieve from this unified repository.

Best for

Best for
Developers building AI agents that need access to a curated personal knowledge base from scattered online sources.

Use cases

  • Aggregating bookmarks and notes from multiple sources into a single searchable store
  • Enabling AI assistants to answer questions based on a user's curated content collection
  • Building a personal knowledge graph from saved digital media and documents

Notes

Braintube-mcp compiles saved YouTube videos, podcasts, articles, PDFs, and notes from Notion or Obsidian into a persistent, semantically organized knowledge base. It runs as an MCP server built in TypeScript, enabling AI agents to query and retrieve from this unified repository.

0 stars on GitHub. Last updated 2026-07-09.

Use cases

  • Aggregating bookmarks and notes from multiple sources into a single searchable store
  • Enabling AI assistants to answer questions based on a user’s curated content collection
  • Building a personal knowledge graph from saved digital media and documents

Pros

  • Unifies diverse content types (video, audio, PDFs, notes) into one persistent store
  • Leverages semantic organization for context-aware retrieval
  • Open source and extendable via MCP protocol

Cons

  • Zero GitHub stars suggests very early stage or limited adoption
  • Requires self-hosting and setup of the MCP server
  • Dependency on external services (YouTube, Notion, Obsidian) for content ingestion

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Unifies diverse content types (video, audio, PDFs, notes) into one persistent store
  • Leverages semantic organization for context-aware retrieval
  • Open source and extendable via MCP protocol

Cons

  • Zero GitHub stars suggests very early stage or limited adoption
  • Requires self-hosting and setup of the MCP server
  • Dependency on external services (YouTube, Notion, Obsidian) for content ingestion
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