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farhankhwaja/codesherpa

Git-native structural memory for AI coding agents. Index once — stays fresh on every pull, merge, and branch switch. MCP server for Claude Code, Cursor & any agent.

4 stars
0 forks
Python
momentum ▲ 8.0
created 2026-07-04
on radar since 2026-07-10
ai-agentscode-searchdeveloper-toolsmcpragretrievalsqlitetree-sitter
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About codesherpa

A git-native, self-updating structural memory for your codebase. Index once, stay fresh forever, and let any LLM agent retrieve exactly the code context it needs over MCP — function-level chunks under a token budget instead of grep-and-read-the-whole-file.

Benchmarks with receipts: see EVALLOG.md — including the target we missed.

- Package & imports: codesherpa (PyPI release imminent — until then, install from GitHub) - Command line & MCP server: sherpa · index lives in .sherpa/

That's it. init installs post-commit/post-checkout/post-merge/ post-rewrite hooks that run sherpa sync --quiet, so the index follows your HEAD automatically. First run downloads the embedding model (~0.5 GB, one-time) to ~/.cache/sherpa/ and prints progress; after that everything is fully local and offline. Try it from the shell with sherpa search "where is the retry logic for http requests".

Agents burn most of their context window navigating: grepping, opening whole files, re-reading. sherpa gives them seven MCP tools that answer structurally:

tool what it answers ------ searchcode(query, budgettokens) hybrid lexical+semantic+symbol search, packed to a token budget getdefinition(symbol) jump to a definition with signature + breadcrumb getcallers(symbol) / getreferences(symbol) ranked callers / references (same-package first) getrecentchanges(since) commits + symbol-level diffs since a ref or ISO date expand(expandid) full body of any compact result, on demand indexstatus() freshness, counts, warming state

From the project README.

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