xdotech

xdotech / goatlas

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GoAtlas: The AI-Powered Code Intelligence Engine — A server-side MCP platform that deeply indexes Go/TypeScript codebases via AST parsing, builds a Neo4j knowledge graph, and provides hybrid semantic search (BM25 + pgvector). Features process detection, community clustering, auto-generated docs, and a Gemini AI agent.

22
1
100% credibility
Found Mar 21, 2026 at 22 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
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AI Summary

GoAtlas is an AI-powered code intelligence platform that parses multi-language codebases into searchable knowledge graphs for natural language queries via chat interfaces.

How It Works

1
🔍 Discover GoAtlas

You hear about GoAtlas, a helpful tool that lets you chat with your codebase like talking to a smart friend who knows every corner of your project.

2
🚀 Easy Setup

With one simple command using ready-made containers, everything starts up automatically including storage and thinking brains—no hassle needed.

3
📂 Feed Your Code

Point it to your project folder and watch it scan all your files, understanding functions, connections, and flows without you lifting a finger.

4
🧠 Link a Thinking Helper

Connect a smart AI like Gemini or a local one so it can answer questions about your code in plain English.

5
💬 Start Chatting

Ask natural questions like 'How does payments connect to messaging?' and get clear answers with code snippets and diagrams.

6
📊 Explore Insights

See automatic maps of services, code groups, and execution paths that reveal how everything fits together.

✨ Master Your Codebase

Now you deeply understand your project, spot issues fast, and build confidently—like having an expert teammate always ready.

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Star Growth

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AI-Generated Review

What is goatlas?

GoAtlas is an AI-powered code intelligence engine built in Go that deeply indexes Go, TypeScript/JSX, Python, and Java codebases using AST parsing. It builds a Neo4j knowledge graph for relationships like calls and imports, plus pgvector for hybrid BM25 + semantic search, letting you query code like "how does payment connect to Kafka?" via a Gemini agent or Ollama. Developers get CLI tools to index repos, chat with an agent, generate auto-generated docs, and expose 22 MCP tools for Cursor or Claude Desktop integration.

Why is it gaining traction?

Zero-config auto-discovery reads go.mod or package.json to detect gRPC/Kafka/HTTP connections across services, while process detection traces flows from handlers and community clustering groups related code—features rare in basic linters. Pluggable LLMs (Gemini, Ollama, OpenAI-compatible) and Claude hooks for incremental re-indexing make it seamless for AI-assisted coding, standing out from static analyzers by feeding dynamic context to agents.

Who should use this?

Backend teams maintaining microservices in Go/TypeScript who need to trace cross-service calls or generate wikis from graphs. AI enthusiasts integrating with Cursor/Claude for codebase Q&A, or devs auditing spec coverage against endpoints and methods. Avoid if you're solo on tiny repos—best for medium+ codebases with 100+ files.

Verdict

Try it if you're building go atlas github workflows around MCP agents; the AI-powered ast parsing and community clustering deliver real value out-of-box with Docker setup. At 22 stars and 1.0% credibility score, it's early but well-documented with tests—watch for polish as adoption grows.

(198 words)

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