Octocode MCP Server

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Structural Code Intelligence for AI Agents — MCP Server + Knowledge Graph + Semantic Search

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

<a href="https://glama.ai/mcp/servers/Muvon/octocode"> <img width="300" src="https://glama.ai/mcp/servers/Muvon/octocode/badge" alt="Octocode MCP server" /> </a> </div>

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🤖 Built for AI Agents

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:

• 🔍 Semantic search — Find code by meaning, not keywords
• 🕸️ Knowledge graph — Navigate imports, calls, and dependencies
• 📝 Code signatures — View structure without reading entire files
• 🧭 LSP precision — Go-to-definition, find-references, and hover docs via your language server

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: "Find every call site of this function"
AI: *uses LSP find-references* "process_payment() is called from 4 places:
    checkout.rs:87, refund.rs:134, billing.rs:56, and tests/payment_test.rs:23"

🤔 Why Octocode?

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

# The GraphRAG CLI queries the optional persisted graph
octocode config --graphrag-enabled true
octocode index
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 build a live graph of files, symbols, imports, calls, inheritance, and implementations. The MCP graphrag tool builds this graph lazily from the current source tree, without an index, embeddings, or an LLM. Optional indexed GraphRAG adds semantic file discovery, descriptions, and broader architectural relationships.

🔬 How It Works

Current Source → Tree-sitter AST → Live Symbol Graph ──────────────→ MCP `graphrag`
                                           ↑                              ↑
Indexed Code → Embeddings + Optional LLM → Persisted File Enrichment ─────┘

1. Live AST Graph — tree-sitter extracts file and symbol nodes plus deterministic contains, imports, calls, extends, and implements relationships directly from current source
2. Always-on Graph Navigation — MCP graph lookup, relationship traversal, path finding, and overview work with [graphrag].enabled = false
3. Optional Enrichment — enabling indexed GraphRAG overlays semantic file matches, LLM descriptions, and broader file-level architectural relationships; symbols are never embedded or LLM-generated
4. Hybrid Search — semantic similarity + BM25 full-text search + reranking handles meaning-based code retrieval separately
5. MCP Server — exposes semantic_search, view_signatures, graphrag, and structural_search to any MCP-compatible client

✨ What Makes It Different

	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.

📊 Retrieval Quality

Octocode ships a reproducible retrieval benchmark (benchmark/): 127 curated code-search queries with line-range ground truth, run against octocode's own source (pinned at b1771ba so annotations never drift). The numbers below use a fully local, no-API-key stack — jina-embeddings-v2-base-code via fastembed, no reranker — so they are a floor, not a ceiling:

Config	Hit@5	Hit@10	MRR	NDCG@10	Recall@10
Dense vector only	0.598	0.717	0.485	0.528	0.671
Hybrid, default RRF weights (0.7/0.3)	0.598	0.717	0.485	0.528	0.671
Hybrid, keyword-tuned (0.3/0.7)	0.732	0.835	0.572	0.620	0.807

Tilting RRF fusion toward the BM25/keyword signal — which carries disproportionate weight for code's exact identifiers — lifts Hit@5 by +22% and Recall@10 by +20% at zero added cost.

The benchmark also flags what doesn't help here (full 6-variant matrix in benchmark/RESULTS.md): a generic local cross-encoder reranker (bge-reranker-base) actually regressed results (Hit@5 0.732 → 0.598) — code retrieval needs a code-aware reranker (e.g. voyage:rerank-2.5), not an off-the-shelf one.

git worktree add /tmp/corpus b1771ba        # pin the corpus to the ground-truth commit
CORPUS=/tmp/corpus python3 benchmark/run_matrix.py

See benchmark/README.md for methodology and metric definitions.

🚀 Quick Start

1. Install

# 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

<details> <summary><strong>Other installation methods</strong></summary>

# 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.

</details>

2. Set Up API Keys

# 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)

<details> <summary><strong>Other embedding providers</strong></summary>

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.

</details>

3. Index Your Codebase

cd /your/project
octocode index
# → Indexed 12,847 blocks across 342 files

4. Search Your Code

# 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

5. Connect Your AI Assistant

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.

🔌 MCP Server Integration

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.

Available Tools

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	Always-on file/symbol graph — search nodes, inspect relationships, and find paths without indexing
structural_search	AST pattern matching — find .unwrap() calls, new instantiations, specific patterns
lsp_goto_definition	Jump to a symbol's definition (requires --with-lsp)
lsp_find_references	Find all usages of a symbol across the workspace (requires --with-lsp)
lsp_hover	Type info and documentation for a symbol (requires --with-lsp)
lsp_document_symbols / lsp_workspace_symbols / lsp_completion	File symbols, workspace-wide symbol search, completions (requires --with-lsp)

Enable the LSP tools by starting the server with your language server:

octocode mcp --path /your/project --with-lsp="rust-analyzer"

Conversational AI Examples

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"

Quick Setup

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:

• Claude Desktop: ~/Library/Application Support/Claude/claude_desktop_config.json (macOS)
• Cursor: ~/.cursor/mcp.json or Settings → MCP Servers
• Windsurf: Settings → MCP

📖 Complete MCP Client Setup Guide — Detailed instructions for 15+ clients including VS Code (Cline/Continue), Zed, Replit, and more.

🎯 What Can You Do With It?

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."

🌐 Supported Languages

16 languages with full tree-sitter AST parsing:

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, .cc, .cxx, .c++, .c, .h, .hpp, .hxx, .cppm, .ixx, .mxx, .ccm, .cxxm	Include analysis, class/function extraction, C++20 module support
Ruby	.rb	Class/module extraction, method definitions
Java	.java	Import analysis, class/method extraction
Swift	.swift	Class/struct/protocol extraction, import analysis
Svelte	.svelte	Component structure, script/style block extraction
Lua	.lua	Function and table extraction
CSS	.css	Rule and selector extraction
JSON	.json	Structure analysis, key extraction
Bash	.sh, .bash	Function and variable extraction
Markdown	.md	Document section indexing, header extraction

📚 Documentation

• Getting Started — First steps and basic workflow
• Installation Guide — Detailed methods and building from source
• MCP Client Setup — Connect to Claude, Cursor, Windsurf, and 15+ clients
• MCP Integration — MCP server details and advanced configuration
• Commands Reference — Complete CLI reference
• Configuration — Templates and customization
• API Keys — Provider setup guide
• Architecture — How it works under the hood
• Contributing — Development setup

🔒 Privacy & Security

• 🏠 Local-first — local embedding models available on supported platforms (macOS ARM default builds); cloud providers on all platforms
• 🔐 Secure — API keys stored locally, env vars supported
• 🚫 Respects .gitignore — Never indexes sensitive files
• 🛡️ MCP security — Local-only server, no external network for search
• 📤 Cloud-safe — Embeddings process only metadata, never source code

<details> <summary><strong>📊 Retrieval Quality Benchmark</strong></summary>

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).

<details> <summary><strong>Documentation search</strong> (<code>--mode docs</code>) — Hit@10: 0.953, MRR: 0.776</summary>

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

</details> <details> <summary><strong>Code search</strong> (<code>--mode code</code>) — Hit@10: 0.992, MRR: 0.895</summary>

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

</details>

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.

</details>

🤝 Community & Support

• ⭐ Star us on GitHub — It really helps!
• 🐛 Report Issues
• 💬 Discussions
• 📧 opensource@muvon.io
• 🌐 muvon.io

⚖️ License

Apache License 2.0 — See LICENSE for details.

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mcp-name: io.github.Muvon/octocode