Embgrep
Gives Claude four semantic search tools over your local codebase without needing API keys or vector databases. Uses fastembed with ONNX Runtime to generate embeddings and stores them in SQLite. The index_directory tool chunks code by functions and docs by headings, semantic_search runs natural language queries with cosine similarity ranking, and update_index does incremental reindexing based on SHA-256 hashes. Supports 15+ file types including Python, JavaScript, TypeScript, Rust, Go, and Markdown. Useful when you want Claude to find relevant code or documentation by meaning rather than exact string matches, especially across large projects where keyword search falls short.
- tools
- 4
- transport
- STDIO
- last updated
- Mar 18, 2026
Tools
4 toolsPublic tool metadata for what this MCP can expose to an agent.
index_directoryIndex files in a directory for semantic search
Index files in a directory for semantic search
No parameter schema in public metadata yet.
semantic_searchSearch indexed files using natural language
Search indexed files using natural language
No parameter schema in public metadata yet.
index_statusGet current index statistics
Get current index statistics
No parameter schema in public metadata yet.
update_indexIncremental update — re-index changed files only
Incremental update — re-index changed files only
No parameter schema in public metadata yet.
Sponsors
Agent CaffeineSponsoredClose your lid, come back to finished work
SnugSponsoredThe clipboard manager for the AI eraPromote your product hereReach 125k+ visitors monthly
WaxSponsoredBlock anything with supervision, without erasing your iPhonePromote your product hereReach 125k+ visitors monthly
knobsSponsoredSee your site on any phone, any day, in any languageReadme
embgrep
Local semantic search — embedding-powered grep for files, zero external services.
Search your codebase and documentation by meaning, not just keywords. embgrep indexes files into local embeddings and lets you run semantic queries — no API keys, no cloud services, no vector database servers.
Features
- Local embeddings — Uses fastembed (ONNX Runtime), no API keys needed
- SQLite storage — Single-file index, no external vector DB
- Incremental indexing — Only re-indexes changed files (SHA-256 hash comparison)
- Smart chunking — Function-level splitting for code, heading-level for docs
- MCP native — 4-tool FastMCP server for LLM agent integration
- 15+ file types —
.py,.js,.ts,.java,.go,.rs,.md,.txt,.yaml,.json,.toml, and more
Details
- Repository
- github.com/quartzunit/embgrep
- Categories
- AI & LLM Tools, Search & Web Crawling
- Package
embgrep- Transport
- STDIO
- Registry
- MCP registry, active
More from quartzunit
Related AI & LLM Tools MCP servers
View all
Recite MCPrivradev/recite-mcpLocal MCP server for Recite receipt processing with ledger and memory tools.0stars
Zopafrjandino/zopafNegotiation math engine. Pareto frontier, counteroffer generation, zero LLM tokens.0stars
Nano Banana 2 MCProcnubie/nanobanana-2-mcpNano Banana 2 exposes the Nano Banana 2 image generation model online with prompt presets and quick0starsNano Banana Pro AI MCProcnubie/nanobanana-mcpNano Banana Pro AI image editor free online. Create, edit, and enhance images by Google Gemini AI0stars
HippoDid MCP Serversamethoughts/hippodid-mcp-serverPersistent, structured cloud memory for AI agents. BYOK — bring your own AI key.0stars