whetstone-mcp

# Whetstone A local [MCP](https://modelcontextprotocol.io) server that lets any skill learn from use. Whetstone attaches to an existing skill and maintains a git-tracked, per-skill store of what a user likes (`LEARNINGS`) and what the skill got wrong (`ISSUES`), so the skill can improve from ordinary use without a benchmark, dataset, or eval harness. See [`LEARNING_SKILLS_DESIGN.md`](https://github.com/HrudithL/whetstone/blob/main/LEARNING_SKILLS_DESIGN.md) for the full design. ## Install Requires Python 3.11+. The base install is light and dependency-free at retrieval time: it uses a small, deterministic `hashing` embedding backend (no torch, no network). ```sh pipx install whetstone-mcp # installs the `whetstone` command on your PATH # or: pip install whetstone-mcp # or, run without installing: uvx whetstone-mcp ``` An install (pipx/pip) puts two equivalent console scripts on your PATH — `whetstone` (primary, used throughout this README) and `whetstone-mcp` (same entry point, so `pipx run whetstone-mcp` / `uvx whetstone-mcp` resolve without the short name). Register it with an MCP host (e.g. Claude Code) — point the host at whichever you used: ```sh # if you installed it (pipx/pip): the command is already on PATH claude mcp add whetstone -- whetstone # no install — let uv fetch & run it on demand: claude mcp add whetstone -- uvx whetstone-mcp ``` For higher-quality embeddings, pull in the optional extra and set `embedding_backend = "sentence-transformers"` in config. Match the command to how it's installed: ```sh pipx install "whetstone-mcp[embeddings]" # fresh install, with the extra pipx inject whetstone-mcp sentence-transformers # add to an existing pipx install pip install "whetstone-mcp[embeddings]" # pip ``` ### From source (contributors) ```sh python3 -m venv .venv .venv/bin/pip install -e '.[dev]' ``` ```sh .venv/bin/pip install -e '.[embeddings]' # pulls in sentence-transformers ``` ## Run St…