Comparison

BrainTube vs Glasp

Social highlights vs. private intelligence.

Glasp is a social web highlighter — you mark text on articles, optionally share it publicly, and discover what others highlight. BrainTube is a private, AI-queryable knowledge base. Glasp's value is the social discovery layer; BrainTube's value is depth (transcripts, summaries, semantic search) and MCP-level integration with the AI clients you actually work in.

Glasp turned highlighting into a social network. BrainTube treats highlighting as one input into a private, AI-queryable knowledge base — with first-class video, summaries, and MCP integration into the AI tools you use every day.

BrainTube

  • Private by default — your library, your retrieval
  • Full video and audio transcripts, not just text snippets
  • AI summaries and chapters auto-generated per item
  • Hybrid search you can actually use from any AI client
  • Public sharing optional — Brains, Digests, Notes
  • MCP server — Claude/Cursor/ChatGPT query directly

Glasp

  • Optimized for social — public-first feels weird for personal notes
  • Web articles only; no native video or audio capture
  • AI features are summarizer-wrappers, not corpus retrieval
  • No MCP / no AI-client integration
  • Search is over your highlights, not the underlying corpus
  • Discovery feed is the headline; storage is the side effect
When BrainTube wins

When you want a private knowledge layer that AI clients can query — and you consume video as well as text.

When Glasp wins

When the social discovery of what others highlight is the actual reason you're there.

A real scenario

A writer enjoys Glasp's social feed to see what other people are reading. The same writer keeps her real research private and consumes hours of podcasts a week. BrainTube takes the podcasts, articles, and PDFs into a private corpus the writer queries through Claude — and Glasp stays open in another tab for the social side.

Verdict

Use Glasp for social highlights. Use BrainTube as your private, AI-queryable knowledge layer.

Frequently asked

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