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Semantic code indexer with GraphRAG knowledge graph. Index your codebase, search in natural language, and expose everything via MCP so AI agents understand arch
Semantic code indexer with GraphRAG knowledge graph. Index your codebase, search in natural language, and expose everything via MCP so AI agents understand architecture — not just files.
GitHub stars License Rust Release
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.
🚀 Quick Start • 🤖 MCP Integration • 📖 Documentation • 🌐 Website
The Problem: AI assistants are blind to your codebase. They can't search your files, understand dependencies, or remember context across sessions.
The Solution: Octocode's MCP server gives AI agents:
Works with: Claude Desktop • Cursor • Windsurf • Any MCP-compatible AI
// Add to your AI assistant config
{
"mcpServers": {
"octocode": {
"command": "octocode",
"args": ["mcp", "--path", "/your/project"]
}
}
}
Now your AI assistant can:
You: "Where is authentication handled?"
AI: *searches your codebase* "Authentication is in src/middleware/auth.rs,
which imports jwt.rs for token validation and calls user_store.rs for lookup."
You: "What files depend on the payment module?"
AI: *queries knowledge graph* "src/api/handlers/payment.rs imports payment/mod.rs,
which is also used by src/workers/refund.rs and src/cron/billing.rs"
You: "Remember this bug fix for future reference"
AI: *stores in memory* "Got it. I'll remember this authentication bypass fix
and apply similar patterns when reviewing security code."
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.
# Semantic search finds the right code
octocode search "authentication middleware"
→ src/middleware/auth.rs | Similarity 0.923
# GraphRAG reveals the full dependency chain
octocode graphrag get-relationships --node_id src/middleware/auth.rs
Outgoing:
imports → jwt (src/auth/jwt.rs): token validation logic
calls → user_store (src/db/user_store.rs): user lookup by token
Incoming:
imports ← router (src/router.rs): wires auth into the request pipeline
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.
Source Code → Tree-sitter AST → Symbols & Relationships → Knowledge Graph
↓
Embeddings + Hybrid Search + Reranking → MCP Server
imports, calls, implements, extends, configures, and 9 more types — each with importance weightingsemantic_search, view_signatures, and graphrag tools to any MCP-compatible client| Standard RAG | Doc Lookup Tools | Octocode | |
|---|---|---|---|
| Indexes | Text chunks | External library docs | Your codebase structure (AST) |
| Understands | Similar text | API specs & usage | Functions, imports, dependencies |
| Cross-file | No | No | Yes — navigates the dependency graph |
| Relationships | No | No | imports, calls, implements, extends... |
| AI integration | Varies | MCP | Native MCP server + LSP |
Doc tools give AI the manual for libraries you use. Octocode gives AI the blueprint of how you put them together.
Built with Rust for performance. Local-first for privacy. Open source (Apache 2.0) for transparency.
# Universal installer (Linux, macOS, Windows)
curl -fsSL https://raw.githubusercontent.com/Muvon/octocode/master/install.sh | sh
# macOS with Homebrew
brew install muvon/tap/octocode
# Cargo (build from source)
cargo install --git https://github.com/Muvon/octocode
# Download binary from releases
# https://github.com/Muvon/octocode/releases
See Installation Guide for platform-specific instructions.
# Required: Embedding provider (Voyage AI has 200M free tokens/month)
export VOYAGE_API_KEY="your-voyage-api-key"
# Optional: LLM for commit messages, code review
export OPENROUTER_API_KEY="your-openrouter-api-key"
Get your Voyage API key: voyageai.com (free tier available)
Octocode supports multiple embedding providers:
# OpenAI
export OPENAI_API_KEY="your-key"
octocode config --code-embedding-model "openai:text-embedding-3-small"
# Jina AI
export JINA_API_KEY="your-key"
octocode config --code-embedding-model "jina:jina-embeddings-v3"
# Google
export GOOGLE_API_KEY="your-key"
octocode config --code-embedding-model "google:text-embedding-005"
See API Keys guide for all supported providers.
cd /your/project
octocode index
# → Indexed 12,847 blocks across 342 files
# Natural language search
octocode search "authentication middleware"
# Multi-query for broader results
octocode search "auth" "middleware" "session"
# Filter by language
octocode search "database connection pool" --lang rust
# Search commit history
octocode search "authentication refactor" --mode commits
Add to your MCP client config (Claude Desktop, Cursor, Windsurf):
{
"mcpServers": {
"octocode": {
"command": "octocode",
"args": ["mcp", "--path", "/your/project"]
}
}
}
Done! Your AI assistant now understands your codebase structure.
Octocode includes a built-in MCP server that exposes your codebase as tools to AI assistants. This is the primary way to use Octocode — give your AI assistant direct access to search and navigate your code.
| Tool | What It Does |
|---|---|
semantic_search |
Find code by meaning — "authentication flow", "error handling", "database queries" |
view_signatures |
View file structure — function signatures, class definitions, imports |
graphrag |
Query relationships — "what calls this function?", "what does this module import?" |
structural_search |
AST pattern matching — find .unwrap() calls, new instantiations, specific patterns |
Once connected, your AI assistant can answer questions about your codebase:
You: "Where is user authentication implemented?"
AI: *uses semantic_search* "Found in src/auth/login.rs. The authenticate() function
validates credentials against the database, generates a JWT token, and stores
the session in Redis."
You: "What files depend on the payment module?"
AI: *uses graphrag* "src/api/handlers/payment.rs imports payment/mod.rs, which is also
used by src/workers/refund.rs and src/cron/billing.rs. The payment module exports
process_payment() and validate_transaction() functions."
You: "Show me all error handling in the API layer"
AI: *uses structural_search* "Found 23 error handling patterns in src/api/:
- 15 use Result<T, ApiError> with explicit error types
- 8 use .unwrap() (potential panics in handlers/user.rs:42, handlers/auth.rs:87)
- 3 use .expect() with custom messages"
Octomind (Recommended) — Zero setup, Octocode pre-configured:
curl -fsSL https://raw.githubusercontent.com/muvon/octomind/master/install.sh | bash
octomind run developer:rust
Claude Code (CLI) — Command-line setup:
claude mcp add octocode -- octocode mcp --path /path/to/your/project
Claude Desktop / Cursor / Windsurf — Add to config:
{
"mcpServers": {
"octocode": {
"command": "octocode",
"args": ["mcp", "--path", "/path/to/your/project"]
}
}
}
Config locations:
~/Library/Application Support/Claude/claude_desktop_config.json (macOS)~/.cursor/mcp.json or Settings → MCP Servers📖 Complete MCP Client Setup Guide — Detailed instructions for 15+ clients including VS Code (Cline/Continue), Zed, Replit, and more.
New developer onboarding:
You: "How does the authentication system work?"
AI: *searches and navigates* "Authentication starts in src/middleware/auth.rs which
validates JWT tokens. It calls src/auth/jwt.rs for token verification, which uses
the public key from config. Failed auth returns 401 via src/errors/auth_error.rs.
Sessions are stored in Redis via src/cache/session.rs."
Code archaeology:
You: "Find all places we handle database errors"
AI: *structural search* "Found 47 error handling patterns:
- 32 use Result<T, DbError> with proper error types
- 15 use .unwrap() (potential issues in src/db/user.rs:23, src/db/order.rs:156)
- Recommend adding proper error handling to those locations"
Refactoring with confidence:
You: "What depends on the PaymentProcessor trait?"
AI: *queries graph* "src/api/handlers/checkout.rs, src/workers/refund_worker.rs,
and src/cron/billing.rs all depend on PaymentProcessor. The trait is defined
in src/domain/payment.rs and implemented by src/infrastructure/stripe.rs
and src/infrastructure/paypal.rs."
Code review assistance:
You: "Review this PR for security issues"
AI: *analyzes changes* "The PR adds password hashing in src/auth/hash.rs. However,
it uses SHA256 which is fast and vulnerable to brute force. Recommend using
bcrypt or argon2 instead. Also found 3 instances of .unwrap() that could panic
in production."
| Language | Extensions | Features |
|---|---|---|
| Rust | .rs |
Full AST parsing, pub/use detection, module structure |
| Python | .py |
Import/class/function extraction, docstring parsing |
| TypeScript/JavaScript | .ts, .tsx, .js, .jsx |
ES6 imports/exports, type definitions |
| Go | .go |
Package/import analysis, struct/interface parsing |
| PHP | .php |
Class/function extraction, namespace support |
| C++ | .cpp, .hpp, .h |
Include analysis, class/function extraction |
| Ruby | .rb |
Class/module extraction, method definitions |
| Java | .java |
Import analysis, class/method extraction |
| JSON | .json |
Structure analysis, key extraction |
| Bash | .sh, .bash |
Function and variable extraction |
| Markdown | .md |
Document section indexing, header extraction |
Plus: CSS, Lua, Svelte, and more via tree-sitter
We measure semantic search quality using a hand-annotated ground truth dataset of 254 queries (127 code + 127 docs) with precise line-range annotations. Each query has 1–3 expected results scored by relevance.
Tested on commit b1771ba with benchmark config (contextual retrieval, Voyage reranker, RaBitQ quantization).
--mode docs) — Hit@10: 0.953, MRR: 0.776| Metric | Score |
|---|---|
| Hit@5 | 0.929 (118/127) |
| Hit@10 | 0.953 (121/127) |
| MRR | 0.776 |
| NDCG@10 | 0.801 |
| Recall@5 | 0.902 |
| Recall@10 | 0.921 |
Missed queries (6 of 127):
| # | Query | Expected | Got (top 1) |
|---|---|---|---|
| 43 | how to set up MCP proxy for managing multiple repositories | doc/MCP_INTEGRATION.md:286-311 |
doc/MCP_INTEGRATION.md:286-4 |
| 51 | what are the prerequisites before using octocode | doc/GETTING_STARTED.md:6-12 |
doc/CONTRIBUTING.md:7-33 |
| 59 | what to do when hitting API rate limits | doc/GETTING_STARTED.md:209-216 |
doc/PERFORMANCE.md:304-356 |
| 75 | typical performance metrics for small medium and large projects | doc/PERFORMANCE.md:4-13 |
doc/PERFORMANCE.md:414-14 |
| 112 | how to install octocode on different operating systems | INSTALL.md:4-14 |
INSTALL.md:49-70 |
| 115 | how to fix macOS Gatekeeper blocking the binary | INSTALL.md:199-206 |
INSTALL.md:198-119 |
--mode code) — Hit@10: 0.992, MRR: 0.895| Metric | Score |
|---|---|
| Hit@5 | 0.992 (126/127) |
| Hit@10 | 0.992 (126/127) |
| MRR | 0.895 |
| NDCG@10 | 0.906 |
| Recall@5 | 0.962 |
| Recall@10 | 0.974 |
Missed queries (1 of 127):
| # | Query | Expected | Got (top 1) |
|---|---|---|---|
| 105 | how does the system ensure two developers get the same database path | src/storage.rs:60-83 |
src/mcp/proxy.rs:631-644 |
Metrics: Hit@k (did the answer appear?), MRR (how high?), NDCG@10 (are best results ranked first?), Recall@k (how many found?). See benchmark/ for methodology, scoring script, and the full dataset.
Apache License 2.0 — See LICENSE for details.
Добавь это в claude_desktop_config.json и перезапусти Claude Desktop.
{
"mcpServers": {
"muvon-octocode": {
"command": "npx",
"args": []
}
}
}