AutoDev Codebase MCP Server

AutoDev Codebase MCP Server

HTTP-based server that provides semantic code search capabilities to IDEs through the Model Context Protocol, allowing efficient codebase exploration without repeated indexing.

Category
Visit Server

README

@autodev/codebase

<div align="center"> <img src="src/images/image1.png" width="300" alt="Image 1" style="margin: 0 10px;" /> <img src="src/images/image2.png" width="200" alt="Image 2" style="margin: 0 10px;" /> <img src="src/images/image3.png" height="150" alt="Image 3" style="margin: 0 10px;" /> </div>

<br />

A platform-agnostic code analysis library with semantic search capabilities and MCP (Model Context Protocol) server support. This library provides intelligent code indexing, vector-based semantic search, and can be integrated into various development tools and IDEs.

🚀 Features

  • Semantic Code Search: Vector-based code search using embeddings
  • MCP Server Support: HTTP-based MCP server for IDE integration
  • Terminal UI: Interactive CLI with rich terminal interface
  • Tree-sitter Parsing: Advanced code parsing and analysis
  • Vector Storage: Qdrant vector database integration
  • Flexible Embedding: Support for various embedding models via Ollama

📦 Installation

1. Install and Start Ollama

# Install Ollama (macOS)
brew install ollama

# Start Ollama service
ollama serve

# In a new terminal, pull the embedding model
ollama pull nomic-embed-text

2. Install and Start Qdrant

Start Qdrant using Docker:

# Start Qdrant container
docker run -p 6333:6333 -p 6334:6334 qdrant/qdrant

Or download and run Qdrant directly:

# Download and run Qdrant
wget https://github.com/qdrant/qdrant/releases/latest/download/qdrant-x86_64-unknown-linux-gnu.tar.gz
tar -xzf qdrant-x86_64-unknown-linux-gnu.tar.gz
./qdrant

3. Verify Services Are Running

# Check Ollama
curl http://localhost:11434/api/tags

# Check Qdrant
curl http://localhost:6333/collections

4. Install project locally

git clone https://github.com/anrgct/autodev-codebase
cd autodev-codebase
npm install
npm run build
npm link

🛠️ Usage

Command Line Interface

The CLI provides two main modes:

1. Interactive TUI Mode (Default)

# Basic usage: index your current folder as the codebase.
# Be cautious when running this command if you have a large number of files.
codebase


# With custom options
codebase --demo # Create a local demo directory and test the indexing service, recommend for setup
codebase --path=/my/project
codebase --path=/my/project --log-level=info

2. MCP Server Mode (Recommended for IDE Integration)

# Start long-running MCP server
cd /my/project
codebase mcp-server

# With custom configuration
codebase mcp-server --port=3001 --host=localhost
codebase mcp-server --path=/workspace --port=3002

IDE Integration (Cursor/Claude)

Configure your IDE to connect to the MCP server:

{
  "mcpServers": {
    "codebase": {
      "url": "http://localhost:3001/sse"
    }
  }
}

Library Usage

Node.js Usage

import { createNodeDependencies } from '@autodev/codebase/adapters/nodejs'
import { CodeIndexManager } from '@autodev/codebase'

const deps = createNodeDependencies({ 
  workspacePath: '/path/to/project',
  storageOptions: { /* ... */ },
  loggerOptions: { /* ... */ },
  configOptions: { /* ... */ }
})

const manager = CodeIndexManager.getInstance(deps)
await manager.initialize()
await manager.startIndexing()

🔧 CLI Options

Global Options

  • --path=<path> - Workspace path (default: current directory)
  • --demo - Create demo files in workspace
  • --ollama-url=<url> - Ollama API URL (default: http://localhost:11434)
  • --qdrant-url=<url> - Qdrant vector DB URL (default: http://localhost:6333)
  • --model=<model> - Embedding model (default: nomic-embed-text)
  • --config=<path> - Config file path
  • --storage=<path> - Storage directory path
  • --cache=<path> - Cache directory path
  • --log-level=<level> - Log level: error|warn|info|debug (default: error)
  • --help, -h - Show help

MCP Server Options

  • --port=<port> - HTTP server port (default: 3001)
  • --host=<host> - HTTP server host (default: localhost)

🌐 MCP Server Features

Web Interface

  • Home Page: http://localhost:3001 - Server status and configuration
  • Health Check: http://localhost:3001/health - JSON status endpoint
  • MCP Endpoint: http://localhost:3001/sse - SSE/HTTP MCP protocol endpoint

Available MCP Tools

  • search_codebase - Semantic search through your codebase
    • Parameters: query (string), limit (number), filters (object)
    • Returns: Formatted search results with file paths, scores, and code blocks
  • get_search_stats - Get indexing status and statistics
  • configure_search - Configure search parameters at runtime

Scripts

# Development mode with demo files
npm run dev

# Build for production
npm run build

# Type checking
npm run type-check

# Run TUI demo
npm run demo-tui

# Start MCP server demo
npm run mcp-server

💡 Why Use MCP Server Mode?

Problems Solved

  • ❌ Repeated Indexing: Every IDE connection re-indexes, wasting time and resources
  • ❌ Complex Configuration: Each project needs different path parameters in IDE
  • ❌ Resource Waste: Multiple IDE windows start multiple server instances

Benefits

  • ✅ One-time Indexing: Server runs long-term, index persists
  • ✅ Simplified Configuration: Universal IDE configuration, no project-specific paths
  • ✅ Resource Efficiency: One server instance per project
  • ✅ Better Developer Experience: Start server in project directory intuitively
  • ✅ Backward Compatible: Still supports traditional per-connection mode
  • ✅ Web Interface: Status monitoring and configuration help
  • ✅ Dual Mode: Can run both TUI and MCP server simultaneously

This is a platform-agnostic library extracted from the roo-code VSCode plugin.

📚 Examples

See the examples/ directory for complete usage examples:

  • nodejs-usage.ts - Node.js integration examples
  • run-demo-tui.tsx - TUI demo application

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured