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