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Semantic code search for AI — ripgrep speed with tree-sitter AST parsing.
zvec-grep ist ein Open-Source-Projekt aus der Kategorie Entwickler-Tools von zvec-ai (zvec-ai/zvec-grep auf GitHub). Es hat 3.994 Sterne auf GitHub und 235 Forks, wird unter der Lizenz Apache-2.0 veröffentlicht und wurde zuletzt am 8. Oktober 2026 auf GitHub aktualisiert.
zvec-grep (zg): one local CLI unifying ripgrep-style exact search, BM25, and semantic vector search
Choose the codebase or document set you want searchable by meaning, not just by string.
Install the CLI globally from npm (Node.js 22+).
Run zg index with a local embedding model to create the .zvec-grep/ index.
Query with --human for readable, cited results, or wire zg into your agent via its installer/MCP tools.
Exact (ripgrep-style), BM25, and vector/semantic search behind a single interface.
Symbol-aware code search plus document and structured-data search.
Ranked answers link back to source files and lines.
Indexes live in .zvec-grep/; local embedding models keep data on your machine by default.
One-command installs into agent tools (for example OpenCode) and MCP tool exposure.
Index once, then query repeatedly without re-embedding the corpus.
Clone the project and enter its directory (CLI users can install from npm instead).
git clone https://github.com/zvec-ai/zvec-grep.git
cd zvec-grepInstall zg globally from npm (Node.js 22+ required).
npm install -g @zvec/zvec-grepBuild an index with a local embedding model, then ask a question.
zg index --embedding local/potion-retrieval-32m
zg query --human "where is authentication handled?" --limit 3zvec-ai develops zvec-grep (the zvec vector-search project team).
Yes, Apache-2.0 licensed and local-first.
No — local embedding models are supported and are the default posture; remote embeddings are used only with your permission.
ripgrep finds exact strings. zg keeps that, adds BM25 ranking and semantic vector search, and returns ranked results with citations — at the cost of building an index first.
Run `npm install -g @zvec/zvec-grep`, `zg index` in your project, then `zg query --human "your question"`.
Semantic code search for AI — ripgrep speed with tree-sitter AST parsing.
Fast, accurate semantic code search for agents — about 99% fewer tokens than grep plus read.
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