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jamon8888/basemind

v0.29.3MIT

Full AI context layer over MCP — tree-sitter code-map, document RAG (PDF/Office/HTML/email + OCR + reranker), shared agent memory, on-demand web crawl, git history + blame + per-symbol diff. 300+ languages, 10+ coding-agent harnesses, content-addressed Fjall + LanceDB.

basemind-documents

Semantic + full-text search over documents and the web via basemind's RAG store — PDFs, Office, HTML, email, images (OCR), plus scraped/crawled web pages, with cross-encoder reranking, keyword and named-entity (NER) filters, and per-document summaries. Reach for it whenever the user asks to "search the docs / PDFs", "find where a topic is discussed", "pull this URL into context", or "what does the documentation say about X".

Read SKILL.md at the source

Pinned to revision 41d536169363, so it is the text this page describes rather than whatever the author pushed since.

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