octocode
starsforks
How to install octocode?
muvon/octocode
$git clone https://github.com/Muvon/octocodeGive your AI assistant a brain for your codebase. Octocode transforms your project into a navigable knowledge graph that Claude, Cursor, and other AI agents can search, understand, and navigate.
README.md
| 1 | <div align="center"> |
| 2 | |
| 3 | <img src="https://raw.githubusercontent.com/Muvon/octocode/master/logo.svg" width="240" alt="Octocode"> |
| 4 | |
| 5 | ### **Structural Code Intelligence for AI Agents — MCP Server + Knowledge Graph + Semantic Search** |
| 6 | |
| 7 | [](https://github.com/Muvon/octocode/stargazers) |
| 8 | [](https://opensource.org/licenses/Apache-2.0) |
| 9 | [](https://www.rust-lang.org) |
| 10 | [](https://github.com/Muvon/octocode/releases) |
| 11 | |
| 12 | **Give your AI assistant a brain for your codebase.** Octocode transforms your project into a navigable knowledge graph that Claude, Cursor, and other AI agents can search, understand, and navigate. |
| 13 | |
| 14 | [🚀 Quick Start](#-quick-start) • [🤖 MCP Integration](#-mcp-server-integration) • [📖 Documentation](#-documentation) • [🌐 Website](https://octocode.muvon.io) |
| 15 | |
| 16 | <a href="https://glama.ai/mcp/servers/Muvon/octocode"> |
| 17 | <img width="300" src="https://glama.ai/mcp/servers/Muvon/octocode/badge" alt="Octocode MCP server" /> |
| 18 | </a> |
| 19 | |
| 20 | </div> |
| 21 | |
| 22 | --- |
| 23 | |
| 24 | ## 🤖 Built for AI Agents |
| 25 | |
| 26 | **The Problem:** AI assistants are blind to your codebase. They can't search your files, understand dependencies, or remember context across sessions. |
| 27 | |
| 28 | **The Solution:** Octocode's MCP server gives AI agents: |
| 29 | - 🔍 **Semantic search** — Find code by meaning, not keywords |
| 30 | - 🕸️ **Knowledge graph** — Navigate imports, calls, and dependencies |
| 31 | - 📝 **Code signatures** — View structure without reading entire files |
| 32 | - 🧠 **Persistent memory** — Remember decisions across conversations |
| 33 | |
| 34 | **Works with:** Claude Desktop • Cursor • Windsurf • Any MCP-compatible AI |
| 35 | |
| 36 | ```json |
| 37 | // Add to your AI assistant config |
| 38 | { |
| 39 | "mcpServers": { |
| 40 | "octocode": { |
| 41 | "command": "octocode", |
| 42 | "args": ["mcp", "--path", "/your/project"] |
| 43 | } |
| 44 | } |
| 45 | } |
| 46 | ``` |
| 47 | |
| 48 | Now your AI assistant can: |
| 49 | ``` |
| 50 | You: "Where is authentication handled?" |
| 51 | AI: *searches your codebase* "Authentication is in src/middleware/auth.rs, |
| 52 | which imports jwt.rs for token validation and calls user_store.rs for lookup." |
| 53 | |
| 54 | You: "What files depend on the payment module?" |
| 55 | AI: *queries knowledge graph* "src/api/handlers/payment.rs imports payment/mod.rs, |
| 56 | which is also used by src/workers/refund.rs and src/cron/billing.rs" |
| 57 | |
| 58 | You: "Remember this bug fix for future reference" |
| 59 | AI: *stores in memory* "Got it. I'll remember this authentication bypass fix |
| 60 | and apply similar patterns when reviewing security code." |
| 61 | ``` |
| 62 | |
| 63 | ## 🤔 Why Octocode? |
| 64 | |
| 65 | **Standard RAG treats your code as flat text chunks.** It finds similar-sounding snippets but has no idea that `auth_middleware.rs` imports `jwt.rs`, calls `user_store.rs`, and is wired into `router.rs`. Octocode understands *structure*. |
| 66 | |
| 67 | ``` |
| 68 | # Semantic search finds the right code |
| 69 | octocode search "authentication middleware" |
| 70 | → src/middleware/auth.rs | Similarity 0.923 |
| 71 | |
| 72 | # GraphRAG reveals the full dependency chain |
| 73 | octocode graphrag get-relationships --node_id src/middleware/auth.rs |
| 74 | Outgoing: |
| 75 | imports → jwt (src/auth/jwt.rs): token validation logic |
| 76 | calls → user_store (src/db/user_store.rs): user lookup by token |
| 77 | Incoming: |
| 78 | imports ← router (src/router.rs): wires auth into the request pipeline |
| 79 | ``` |
| 80 | |
| 81 | Octocode uses **tree-sitter AST parsing** to extract real symbols (functions, imports, dependencies), builds a **GraphRAG knowledge graph** of relationships between files, and exposes everything via **MCP** — so AI tools can *navigate* your project architecture, not just search it. |
| 82 | |
| 83 | ## 🔬 How It Works |
| 84 | |
| 85 | ``` |
| 86 | Source Code → Tree-sitter AST → Symbols & Relationships → Knowledge Graph |
| 87 | ↓ |
| 88 | Embeddings + Hybrid Search + Reranking → MCP Server |
| 89 | ``` |
| 90 | |
| 91 | 1. **AST Parsing** — tree-sitter extracts real code symbols (functions, classes, imports), not arbitrary text chunks |
| 92 | 2. **Knowledge Graph** — GraphRAG maps rela |
People who liked this also viewed
6 picksType
- fastapi_mcpExpose your FastAPI endpoints as Model Context Protocol (MCP) tools, with Auth!MCP ServersNov 2025
- lean-lsp-mcpLean Theorem Prover MCPMCP ServersJul 2026
- rulesyncA Utility CLI for AI Coding AgentsMCP ServersJul 2026
- FunASROpen-source speech recognition toolkit for training, inference, streaming ASR, VAD, punctuation, speaker diarization pipelines, and OpenAI-compatible/MCP serving.MCP ServersJul 2026
- repomix📦 Repomix is a powerful tool that packs your entire repository into a single, AI-friendly file. Perfect for when you need to feed your codebase to Large Language Models (LLMs) or other AI tools like Claude, ChatGPT, DeepSeek, Perplexity, Gemini, Gemma, Llama, Grok, and more.MCP ServersJul 2026
- mcp-serverMCP server for AI-assisted development of CAP applicationsMCP ServersJul 2026
