GoAtlas 是一个由人工智能驱动的代码智能平台，帮助大型语言模型和开发者深入理解大型代码库——结合了多语言 AST 解析、Neo4j 知识图、pgvector 语义搜索和可插拔的 LLM 后端，所有这些都通过 模型上下文协议（MCP） 公开。

它有什么不同

• 多语言 — 通过 AST（树置法）解析 Go、TypeScript/JSX、Python 和 Java;每种语言提取符号、端点和导入
• 零配置自动发现 — 读取 go.mod、package.json、requirements.txt、pom.xml]，自动激活 gRPC、Kafka、HTTP 客户端等的连接检测模式
• 跨服务连接检测 — 检测跨Go、TS、Python和Java的服务间连接（gRPC、Kafka、HTTP），无需配置
• 知识图谱 — 包含包、文件、函数、类型的 Neo4j 图，带有导入/调用/实现边缘
• 混合BM25 + 语义搜索 — 互易秩融合合并关键词和向量结果;通过Gemini或Ollama嵌入实现语义搜索
• 进程与社区检测 — 来自入口点的BFS追踪执行流程;鲁汶集群组代码社区

GoAtlas

GoAtlas is an AI-powered code intelligence platform that helps LLMs and developers deeply understand large codebases — combining multi-language AST parsing, a Neo4j knowledge graph, pgvector semantic search, and a pluggable LLM backend, all exposed via the Model Context Protocol (MCP).

What Makes It Different

• Multi-Language — Go, TypeScript/JSX, Python, and Java parsed via AST (tree-sitter); symbols, endpoints, imports extracted per language
• Zero-Config Auto-Discovery — Reads go.mod, package.json, requirements.txt, pom.xml to automatically activate connection detection patterns for gRPC, Kafka, HTTP clients, and more
• Cross-Service Connection Detection — Detects inter-service connections (gRPC, Kafka, HTTP) across Go, TS, Python, and Java with no config required
• Knowledge Graph — Neo4j graph of packages, files, functions, types with import/call/implementation edges
• Hybrid BM25 + Semantic Search — Reciprocal Rank Fusion merges keyword and vector results; semantic search via Gemini or Ollama embeddings
• Process & Community Detection — BFS from entry points traces execution flows; Louvain clustering groups code communities
• Pluggable LLM — Supports Gemini (gemini-2.0-flash), Ollama (any local model), and any OpenAI-compatible API (vLLM, LiteLLM, etc.) for both embeddings and agentic Q&A
• MCP Server — 22 tools, 5 resources, 3 prompts via stdio for Cursor, Claude Desktop, and any MCP client
• Claude Code Hooks — SessionStart/PreToolUse/PostToolUse integration for session context injection, semantic enrichment, and incremental re-indexing
• AI-Generated Docs — SKILL.md per community cluster and full Markdown wiki from the knowledge graph

Architecture

graph TB
    subgraph CLI["GoAtlas CLI"]
        direction LR
        IDX["index"]
        EMB["embed"]
        GR["build-graph"]
        DET["detect"]
        ASK["ask"]
        CHT["chat"]
        SRV["serve"]
        SKL["skills"]
        WK["wiki"]
    end

    subgraph Core["Core Engine"]
        direction TB
        PARSER["AST Parsers\nGo · TS/JSX · Python · Java"]
        INDEXER["Code Indexer\nsymbols · endpoints · connections"]