AutoDev Remote AI Agent

A comprehensive Model Context Protocol (MCP) server that provides advanced GitHub issue analysis capabilities with intelligent code context integration. This server can fetch GitHub issues, analyze them with AI-powered insights, and provide relevant code context from your local workspace using the AutoDev ecosystem.

✨ Key Features

• 🔍 GitHub Integration: Fetch, analyze, and interact with GitHub issues from any repository
• 🧠 AI-Powered Analysis: Uses LLM to intelligently extract keywords, generate insights, and create analysis reports
• 🌐 Web Content Processing: Automatically fetch and convert web URLs to markdown using Puppeteer, Cheerio, and TurndownService
• 📊 Code Context Analysis: Analyze your local codebase to find relevant files, symbols, and APIs using advanced search strategies
• 🎯 Multi-Strategy Search: Combines LLM analysis, ripgrep text search, symbol analysis, and relevance scoring
• 📝 Automated Reporting: Generate and upload comprehensive analysis reports directly to GitHub issues
• 🌍 Multi-Language Support: Supports both English and Chinese report generation
• 🏗️ Design Pattern Architecture: Built with Strategy, Factory, and Template Method patterns for extensibility
• ⚡ Smart Caching: Advanced caching system for improved performance
• 🔄 Smart Fallback: Works with or without LLM configuration using rule-based alternatives
• 🔌 MCP Protocol Support: Full Model Context Protocol implementation for seamless AI assistant integration

Installation

Using npx (Recommended)

npx @autodev/remote-agent@latest

Using pnpm

pnpm add -g @autodev/remote-agent

Setup

Environment Variables

Required: GitHub Token

Set your GitHub personal access token:

export GITHUB_TOKEN=your_github_token_here

Optional: LLM Configuration (for AI-powered features)

Option 1: GLM (ZhipuAI) - Recommended

export GLM_TOKEN=your_glm_token_here
export LLM_BASE_URL=https://open.bigmodel.cn/api/paas/v4
export LLM_MODEL=glm-4-air

Option 2: OpenAI

export OPENAI_API_KEY=your_openai_api_key_here
export LLM_BASE_URL=https://api.openai.com/v1
export LLM_MODEL=gpt-4o-mini

Option 3: Other OpenAI-compatible APIs

export LLM_BASE_URL=https://your-api-endpoint.com/v1
export OPENAI_API_KEY=your_api_key_here
export LLM_MODEL=your_model_name

Note: LLM configuration is optional. The system will fall back to rule-based keyword extraction if no LLM is configured.

GitHub Token Setup

1. Go to GitHub Settings > Developer settings > Personal access tokens
2. Generate a new token with the following scopes:
   • repo (for private repositories)
   • public_repo (for public repositories)
   • issues (to read issues)

Usage

Command Line

Start as MCP Server (stdio)

autodev-remote-agent

Start as HTTP Server

autodev-remote-agent --port 3001

Standalone Issue Analysis

autodev-analyze-issue --owner microsoft --repo vscode --issue 12345

Available Tools

The Remote Agent provides the following comprehensive MCP tools:

GitHub Integration Tools

• github_get_issues: Fetch GitHub issues with advanced filtering options
• github_analyze_issue: Analyze issues with AI-powered insights and URL content fetching
• github_get_issue_context: Get detailed context for issues including related code
• github_smart_search: Intelligently search for code related to any query
• github_upload_analysis: Analyze issues and upload results as comments
• github_issue_create: Create new GitHub issues
• github_issue_comment: Add comments to GitHub issues

File System Tools

• read-file: Read file contents with encoding support
• write-file: Create or update files with multiple modes (create/append/overwrite)
• list-directory: List directory contents with filtering options
• delete-file: Delete files from the filesystem
• str-replace-editor: Precise code editing with pattern matching

Code Analysis Tools

• analyze-basic-context: Analyze project structure and context
• search-keywords: Search for keywords across files
• code-search-regex: Search code using regular expressions
• semantic-code-search: AI-powered semantic code search

Terminal & Process Tools

• run-terminal-command: Execute terminal commands with output capture
• get-terminal-output: Get output from previously executed commands
• launch-process: Start background processes with management options
• list-processes: List running processes
• read-process: Get output from running processes
• kill-process: Terminate running processes

Web Tools

• web-fetch-content: Fetch and convert web content to markdown
• web-search: Search the web using Google or Bing APIs
• open-browser: Open URLs in the system browser

🚀 Advanced Capabilities

AI-Powered Analysis

• 🧠 LLM-powered keyword extraction: Uses AI models to intelligently analyze issue descriptions and generate relevant search terms
• 📊 Intelligent relevance scoring: Ranks results by likelihood of being related to your query
• 🎯 Context-aware suggestions: Provides actionable recommendations based on AI-detected issue type
• 📝 Automated report generation: Creates comprehensive analysis reports with detailed plans and recommendations

Multi-Strategy Search

• 🔍 Hybrid search approach: Combines LLM analysis, ripgrep text search, symbol analysis, and relevance scoring
• 📋 Comprehensive analysis: Includes files, symbols, APIs, and detailed explanations
• 🔄 Smart fallback: Works with rule-based extraction when LLM is not configured
• ⚡ Performance optimization: Advanced caching and efficient search algorithms

Web Content Integration

• 🌐 Automatic URL fetching: Extracts and processes URLs from GitHub issues
• 📄 HTML to Markdown conversion: Uses Cheerio and TurndownService for clean content extraction
• 🧹 Content cleaning: Removes scripts, styles, and navigation elements for focused analysis

Web Search Capabilities

• 🔍 Multi-engine search: Supports Google Custom Search and Bing Search APIs with automatic fallback
• 🌍 Multi-language support: Search in different languages (English, Chinese, etc.)
• 🛡️ Safe search filtering: Optional content filtering for appropriate results
• ⚡ Smart error handling: Graceful fallback and detailed error messages with configuration guidance

💡 Usage Examples

Basic Issue Analysis

{
  "tool": "github_analyze_issue",
  "arguments": {
    "owner": "microsoft",
    "repo": "vscode",
    "issue_number": 12345,
    "workspace_path": "/path/to/your/project"
  }
}

Smart Search for Bug Investigation

{
  "tool": "github_smart_search",
  "arguments": {
    "owner": "microsoft",
    "repo": "vscode",
    "query": "TypeError: Cannot read property 'length' of undefined in file explorer",
    "search_depth": "deep"
  }
}

Automated Analysis Upload

{
  "tool": "github_upload_analysis",
  "arguments": {
    "owner": "microsoft",
    "repo": "vscode",
    "issue_number": 12345,
    "language": "zh",
    "include_file_content": true
  }
}

Web Search for Knowledge Verification

{
  "tool": "web-search",
  "arguments": {
    "query": "React Server Components best practices 2024",
    "num_results": 5,
    "search_engine": "auto",
    "language": "en"
  }
}

Integration with AI Assistants

This MCP server can be integrated with AI assistants that support the Model Context Protocol, such as:

• Claude Desktop
• Custom AI applications
• Other MCP-compatible tools

Claude Desktop Configuration

Add to your Claude Desktop MCP configuration:

{
  "mcpServers": {
    "remote-agent": {
      "command": "npx",
      "args": ["@autodev/remote-agent@latest"],
      "env": {
        "GITHUB_TOKEN": "your_github_token_here",
        "GLM_TOKEN": "your_glm_token_here",
        "GOOGLE_SEARCH_API_KEY": "your_google_search_api_key",
        "GOOGLE_SEARCH_ENGINE_ID": "your_google_search_engine_id",
        "BING_SEARCH_API_KEY": "your_bing_search_api_key"
      }
    }
  }
}

🏗️ Architecture & How It Works

Design Patterns Implementation

• Strategy Pattern: Multiple analysis strategies (LLM, rule-based, hybrid) for different scenarios
• Factory Pattern: Dynamic creation of analyzers based on configuration and available resources
• Template Method Pattern: Consistent analysis workflow with customizable steps

Processing Pipeline

1. GitHub API Integration: Uses the GitHub REST API to fetch issue data and repository information
2. Content Processing: Automatically fetches and converts web URLs to markdown using Puppeteer and Cheerio
3. AI Analysis: Leverages LLM services for intelligent keyword extraction and context understanding
4. Code Analysis: Uses the AutoDev context-worker ecosystem to analyze your local codebase
5. Multi-Strategy Search: Combines ripgrep, symbol analysis, and AI-powered relevance scoring
6. Report Generation: Creates comprehensive analysis reports with actionable recommendations
7. GitHub Integration: Optionally uploads analysis results directly to GitHub issues as comments

Caching & Performance

• Advanced caching system: Memory, file, and Redis-based caching options
• Intelligent cache invalidation: Based on issue updates and workspace changes
• Optimized search algorithms: Efficient file filtering and content analysis

📊 Comparison with Other AI Agents

AutoDev Remote Agent has been designed with a comprehensive set of tools that compare favorably with other AI coding agents:

| Feature Category | AutoDev Remote Agent | Other AI Agents | |-----------------|----------------------|----------------| | File Operations | Complete suite (read, write, list, delete) | Often limited to basic operations | | Terminal Execution | Advanced command execution with output analysis | Basic command execution | | Process Management | Full process lifecycle management | Limited or no process management | | Code Search | Multiple search strategies (keywords, regex, semantic) | Basic search capabilities | | GitHub Integration | Complete GitHub workflow tools | Limited or no GitHub integration | | Web Capabilities | Content fetching, web search, browser control | Limited web interaction |

With 23 specialized tools, AutoDev Remote Agent provides one of the most comprehensive tool sets among AI coding agents, particularly excelling in GitHub integration and process management.

Development

Building from Source

git clone https://github.com/unit-mesh/autodev-workbench
cd packages/remote-agent
pnpm install
pnpm build

Running Tests

pnpm test

Contributing

Contributions are welcome! Please read the contributing guidelines and submit pull requests to the main repository.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.