For the last 4 months, I've been programming exclusively with AI. One of the most painful parts has been getting correct and up-to-date documentation for third-party libraries. So I made an agent to fix that.

You can add it as an MCP tool to anything.

It works because it's just focused on doing research for code. You can check out the prompts https://github.com/803/sensei/blob/main/sensei/prompts.py. I combined this with a couple specialized tools for this use-case:

  - Kura - Query cache. Works even better because the prompt instructs the agent to decompose queries into sub-queries, and usually the sub-queries are more generic. Each gets cached as a reusable building block.
  - Scout - Source code explorer. Let's the agent glob, grep, and tree any public repo at any tag/branch/SHA. When docs are unclear or unspecific, there's nothing better than reading what the code actually does.
  - Tome - llms.txt ingestion. Super simple. Does it on-demand for any domain and then stores the results in postgres for search.

I'm not charging for this right now and it's completely open-source and you can run it yourselves with your own API keys. If things go nuts I'll have to change course.

I made it to scratch my itch, maybe it'll scratch yours as well.