Convert source code to LLM ready knowledge base

A semantic code search tool for intelligent, cross-repo context retrieval.

MCP Server for persistent code indexing. Gives AI assistants (Claude, Gemini, Copilot, Cursor) instant access to your codebase. 50x less context than grep.

Self-hosted MCP server for hybrid semantic code search and repository intelligence.

Enhanced fork of claude-context with stability fixes, improved sync, and better reliability for semantic code search

Go-based MCP server for codebase indexing and semantic search (Augment-compatible)

Python application to index code locally and support running server with indexed repos. Works with VoyageAI to power semantic searching a large codebase, enabling AI optimized code navigation. Supports FTS searching, and indexing git log. Experimental support for SCIP indexing.

Give Claude Code a permanent memory — 100% local, zero config, graph-powered

An AI-powered system for intelligent code search, moving beyond keywords to semantic understanding. It offers multi-dimensional search capabilities across files, classes/interfaces, and methods, each with optimized AI-generated embeddings. Get precise, context-aware results to natural language queries quickly and efficiently.

A very simple setup with pgvector, sentencetransformer, and MCP Python SDK, just to bootstrap indexing code files to facilitate RAG-based search for AI coding agents.

Intelligent code indexing and retrieval system for Ruby on Rails projects with MCP integration

Fast code map generator for AI coding assistants - Save 99%+ tokens while preserving context

Code indexing examples for converting source code into structured repository maps optimized for semantic search LLM understanding.

🔍 Convert source code into a searchable knowledge base with automatic chunking and intelligent search, now enhanced with MCP support for better integration.