Top AI Product

If you’ve spent any time watching AI coding assistants fumble through a large codebase, you know the frustration. They miss dependencies, break call chains, and suggest changes that look fine in isolation but wreck something three folders away. The core problem? These tools treat your code as flat text in a context window. They have no real sense of architecture.

[GitNexus](https://github.com/abhigyanpatwari/GitNexus) takes a different approach. Instead of stuffing files into a prompt, it indexes your entire repository into a knowledge graph — mapping out every dependency, call chain, cluster, and execution flow. Then it exposes all of that structure through a built-in Graph RAG Agent and a set of MCP tools that AI assistants like Cursor, Claude Code, and Windsurf can actually use. The result is that your agent stops guessing and starts understanding how your code fits together.

What makes it especially interesting is that the whole thing can run right in your browser. The [web UI](https://gitnexus.vercel.app) uses KuzuDB compiled to WebAssembly alongside Tree-sitter WASM for parsing — no server, no data leaving your machine. You just drop in a GitHub repo URL or a ZIP file and get an interactive graph you can explore visually. For heavier workflows, there’s a CLI (`npx gitnexus analyze`) that indexes locally and persists the graph, plus an MCP server that hands your AI agent seven specialized tools: hybrid search, symbol context lookups, blast radius analysis, git-diff impact mapping, and even coordinated multi-file refactoring. It supports TypeScript, JavaScript, Python, Java, Go, Rust, C, C++, and C# out of the box.

GitNexus hit [GitHub Trending](https://github.com/trending) on Feb 22, 2026, racking up over 1,200 stars with about 132 new ones each day. The buzz is real — developers are excited because this tackles a pain point that flat RAG simply can’t solve. When your agent can query actual graph relationships instead of hoping the right snippet lands in its context window, the quality of suggestions jumps noticeably. I ran it against a mid-sized TypeScript monorepo and the impact analysis alone saved me from a refactor that would have silently broken two downstream services.

It’s free under the PolyForm Noncommercial license, and getting started takes one command. If you’re using any AI-powered coding tool, this is worth fifteen minutes of your time to try.