What is Mcp Unittest Server

The mcp-unittest-server is an MVP server that adheres to the Model Context Protocol (MCP) designed to automatically generate unit tests for source code. It utilizes AI to analyze code and create high-quality unit tests, integrating with continuous development tools and various IDEs.

Use cases

Use cases for the mcp-unittest-server include generating unit tests for existing codebases, enhancing test coverage in continuous integration pipelines, and assisting developers in creating tests for new features or bug fixes efficiently.

How to use

To use the mcp-unittest-server, first install the necessary dependencies and configure any optional AI services. Start the server by activating the virtual environment and running the main Python script. The server will be accessible at http://localhost:5000, where you can interact with it using defined MCP protocol endpoints.

Key features

Key features of the mcp-unittest-server include multi-language support (Python, Java, JavaScript), AI-powered test generation using GPT-4 and Claude, integration with build tools like Maven, Gradle, npm, and pytest, adherence to the MCP protocol for IDE integration, an automatic validation pipeline, and fallback templates for AI unavailability.

Where to use

The mcp-unittest-server can be used in software development environments where automated unit testing is required, particularly in projects that utilize multiple programming languages and require integration with various development tools.

MCP Unit Test Generator Server

Một server MVP tuân thủ Model Context Protocol (MCP) để tự động tạo unit test cho source code, có thể tích hợp với continuedev và các IDE khác.

Tổng quan

MCP Unit Test Generator Server là một công cụ AI-powered giúp tự động phân tích source code và tạo ra các unit test chất lượng cao. Server sử dụng Tree-sitter để phân tích AST (Abstract Syntax Tree) và tích hợp với các LLM services (OpenAI, Anthropic) để tạo test thông minh.

Tính năng chính

• Multi-language Support: Hỗ trợ Python, Java, JavaScript
• AI-powered Test Generation: Sử dụng GPT-4 và Claude để tạo test thông minh
• Build Integration: Tích hợp với Maven, Gradle, npm, pytest
• MCP Protocol: Tuân thủ Model Context Protocol cho tích hợp IDE
• Validation Pipeline: Compile và validate test tự động
• Template Fallback: Fallback templates khi AI không khả dụng

Cài đặt

Yêu cầu hệ thống

• Python 3.11+
• Node.js 20+ (cho JavaScript projects)
• Java 11+ (cho Java projects)
• Git

Cài đặt dependencies

cd mcp_unittest_server
source venv/bin/activate
pip install -r requirements.txt

Cấu hình AI Services (Optional)

export OPENAI_API_KEY="your-openai-api-key"
export ANTHROPIC_API_KEY="your-anthropic-api-key"

Sử dụng

Khởi động server

cd mcp_unittest_server
source venv/bin/activate
python src/main.py

Server sẽ chạy trên http://localhost:5000

MCP Protocol Endpoints

1. Initialize

{
  "method": "initialize",
  "params": {
    "protocolVersion": "2024-11-05",
    "capabilities": {}
  }
}

2. List Tools

{
  "method": "tools/list"
}

3. Call Tool

{
  "method": "tools/call",
  "params": {
    "name": "analyze_code",
    "arguments": {
      "file_path": "/path/to/source.py",
      "language": "python"
    }
  }
}

Direct API Endpoints (for testing)

Analyze Code

curl -X POST http://localhost:5000/analyze \
  -H "Content-Type: application/json" \
  -d '{
    "file_path": "/path/to/source.py",
    "language": "python"
  }'

Generate Tests

curl -X POST http://localhost:5000/generate \
  -H "Content-Type: application/json" \
  -d '{
    "analysis_result": {...},
    "test_framework": "pytest",
    "coverage_target": 80
  }'

Validate Tests

curl -X POST http://localhost:5000/validate \
  -H "Content-Type: application/json" \
  -d '{
    "test_files": ["/path/to/test_file.py"],
    "project_path": "/path/to/project"
  }'

Tích hợp với continuedev

1. Cài đặt MCP client trong continuedev

Thêm vào config của continuedev:

{
  "mcpServers": {
    "unittest-generator": {
      "command": "python",
      "args": [
        "/path/to/mcp_unittest_server/src/main.py"
      ],
      "env": {
        "OPENAI_API_KEY": "your-key"
      }
    }
  }
}

2. Sử dụng trong continuedev

@unittest-generator analyze this file and generate comprehensive unit tests

Kiến trúc

Core Components

1. MCP Server Interface (src/mcp/server.py)

   • Xử lý MCP protocol
   • Tool registration và discovery
   • Request/response handling

2. Code Analyzer (src/parsers/code_analyzer.py)

   • Multi-language AST parsing với Tree-sitter
   • Function/method extraction
   • Complexity analysis

3. Test Generator (src/generators/test_generator.py)

   • AI-powered test generation
   • Template-based fallback
   • Multi-framework support

4. Test Builder (src/builders/test_builder.py)

   • Compilation validation
   • Test execution
   • Error reporting

5. Project Config (src/config/project_config.py)

   • Auto-detect project settings
   • Configuration management

Workflow

Input Code → Code Analysis → Test Generation → Build & Validate → Output Tests
     ↓              ↓              ↓              ↓              ↓
  Tree-sitter    AST Metadata   AI/Templates   Compilation    Validated Tests

Examples

Xem thư mục examples/ để có các ví dụ cụ thể cho từng ngôn ngữ.

Testing

# Run unit tests
python -m pytest tests/

# Test specific component
python -m pytest tests/test_code_analyzer.py

Troubleshooting

Common Issues

1. Tree-sitter compilation errors

   • Đảm bảo có C compiler (gcc/clang)
   • Reinstall tree-sitter packages

2. AI API errors

   • Kiểm tra API keys
   • Verify network connectivity
   • Check API quotas

3. Build tool not found

   • Install Maven/Gradle cho Java
   • Install Node.js cho JavaScript
   • Check PATH environment

Debug Mode

DEBUG=true python src/main.py

Contributing

1. Fork repository
2. Create feature branch
3. Add tests cho new features
4. Submit pull request

License

MIT License - xem file LICENSE để biết chi tiết.

Roadmap

Phase 1 (Current MVP)

• [x] Basic MCP protocol support
• [x] Multi-language parsing
• [x] AI test generation
• [x] Build validation

Phase 2 (Future)

• [ ] Coverage analysis và reporting
• [ ] Dependency graph analysis
• [ ] Advanced test patterns
• [ ] IDE plugins

Phase 3 (Advanced)

• [ ] Machine learning test optimization
• [ ] Continuous integration
• [ ] Team collaboration features
• [ ] Enterprise features