Convert source code to LLM ready knowledge base
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Updated
Dec 30, 2025 - JavaScript
Convert source code to LLM ready knowledge base
A semantic code search tool for intelligent, cross-repo context retrieval.
Deep code indexing MCP server for AI agents. 25 tools: hybrid FTS5 + embedding search, call graphs, git blame/hotspots, build system analysis. Multi-repo workspaces, GPU-accelerated semantic search, 10 languages via tree-sitter. Fully local, zero cloud dependencies.
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.
Multi-agent orchestration, persistent memory, and intelligent workflows for AI coding assistants. Supports Claude Code and OpenCode.
Enhanced fork of claude-context with stability fixes, improved sync, and better reliability for semantic code search
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.
Go-based MCP server for codebase indexing and semantic search (Augment-compatible)
Structured code retrieval for AI agents — index once with tree-sitter, query symbols precisely via MCP. Cut code-reading token costs by up to 99%.
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.
Fast code map generator for AI coding assistants - Save 99%+ tokens while preserving context
Intelligent code indexing and retrieval system for Ruby on Rails projects with MCP integration
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 MCP server. 13 tools, 10 languages, hybrid search, call graphs, O(1) symbol retrieval.
Nuke your token usage. Code indexing MCP server: 15 tools, 10 languages, O(1) retrieval, hybrid search, call graphs.
code-extractor-java is a library designed to scan source code files and extract hierarchical structures such as classes, methods, functions, and comments. It provides a unified model (CodeNode) for representing code regardless of the source language
Code indexing examples for converting source code into structured repository maps optimized for semantic search LLM understanding.
Add a description, image, and links to the code-indexing topic page so that developers can more easily learn about it.
To associate your repository with the code-indexing topic, visit your repo's landing page and select "manage topics."