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.
Project description
basemind
The context and communication layer for coding agents — a shared code-map, document RAG, memory, web crawl, git history, and agent-to-agent comms so multiple agents coordinate while they work. 300+ languages, one MCP server.
Install
pip install basemind
On first invocation, the pre-compiled Rust binary for your platform (macOS, Linux, Windows;
x86_64 + arm64) is downloaded from
GitHub Releases and cached under
~/.cache/basemind/<version>/.
Override the binary location with BASEMIND_BINARY=/path/to/basemind.
Quickstart
cd /path/to/your/repo
basemind scan # index the working tree
basemind serve # run the MCP stdio server
Wire basemind serve into Claude Code or any MCP client.
Full documentation
See the main README for complete docs, architecture, MCP tool reference, and per-harness setup instructions.
License
MIT.
Project details
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