@autodev/codebase

A vector embedding-based code semantic search tool with MCP server and multi-model integration. Can be used as a pure CLI tool. Supports Ollama for fully local embedding and reranking, enabling complete offline operation and privacy protection for your code repository.

# Semantic code search - Find code by meaning, not just keywords
╭─ ~/workspace/autodev-codebase 
╰─❯ codebase search "user manage" --demo
Found 20 results in 5 files for: "user manage"

==================================================
File: "hello.js"
==================================================
< class UserManager > (L7-20)
class UserManager {
  constructor() {
    this.users = [];
  }

  addUser(user) {
    this.users.push(user);
    console.log('User added:', user.name);
  }

  getUsers() {
    return this.users;
  }
}
……

# Call graph analysis - Trace function call relationships and execution paths
╭─ ~/workspace/autodev-codebase 
╰─❯ codebase call --demo --query="app,addUser"
Connections between app, addUser:

Found 2 matching node(s):
  - demo/app:L1-29
  - demo/hello.UserManager.addUser:L12-15

Direct connections:
  - demo/app:L1-29 → demo/hello.UserManager.addUser:L12-15

Chains found:
  - demo/app:L1-29 → demo/hello.UserManager.addUser:L12-15

# Code outline with AI summaries - Understand code structure at a glance
╭─ ~/workspace/autodev-codebase 
╰─❯ codebase outline 'hello.js' --demo --summarize
# hello.js (23 lines)
└─ Defines a greeting function that logs a personalized hello message and returns a welcome string. Implements a UserManager class managing an array of users with methods to add users and retrieve the current user list. Exports both components for external use.

   2--5 | function greetUser
   └─ Implements user greeting logic by logging a personalized hello message and returning a welcome message

   7--20 | class UserManager
   └─ Manages user data with methods to add users to a list and retrieve all stored users

   12--15 | method addUser
   └─ Adds a user to the users array and logs a confirmation message with the user's name.

🚀 Features

• 🔍 Semantic Code Search: Vector-based search using advanced embedding models
• 🔗 Call Graph Analysis: Trace function call relationships and execution paths
• 🌐 MCP Server: HTTP-based MCP server with SSE and stdio adapters
• 💻 Pure CLI Tool: Standalone command-line interface without GUI dependencies
• ⚙️ Layered Configuration: CLI, project, and global config management
• 🎯 Advanced Path Filtering: Glob patterns with brace expansion and exclusions
• 🌲 Tree-sitter Parsing: Support for 40+ programming languages
• 💾 Qdrant Integration: High-performance vector database
• 🔄 Multiple Providers: OpenAI, Ollama, Jina, Gemini, Mistral, OpenRouter, Vercel
• 📊 Real-time Watching: Automatic index updates
• ⚡ Batch Processing: Efficient parallel processing
• 📝 Code Outline Extraction: Generate structured code outlines with AI summaries
• 💨 Dependency Analysis Cache: Intelligent caching for 10-50x faster re-analysis

📦 Installation

1. Dependencies

brew install ollama ripgrep
ollama serve
ollama pull nomic-embed-text

2. Qdrant

docker run -d -p 6333:6333 -p 6334:6334 --name qdrant qdrant/qdrant

3. Install

npm install -g @autodev/codebase
codebase config --set embedderProvider=ollama,embedderModelId=nomic-embed-text

🛠️ Quick Start

# Demo mode (recommended for first-time)
# Creates a demo directory in current working directory for testing

# Index & search
codebase index --demo

... [View full README on GitHub](https://github.com/anrgct/autodev-codebase#readme)