neurodev-mcp

# Clone the repository
git clone https://github.com/ravikant1918/neurodev-mcp.git
cd neurodev-mcp

# Create virtual environment (recommended)
python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\\Scripts\\activate

# Install the package
pip install -e .
\`\`\`

### **Verify Installation**

\`\`\`bash
# Run tests (should show 15/15 passing)
python test_installation.py

# Test the server
python -m neurodev_mcp.server
\`\`\`

📁 Project Structure (click to expand)

\`\`\`
neurodev-mcp/
├─ neurodev_mcp/              # 📦 Main package
│   ├─ __init__.py            # Package exports
│   ├─ server.py              # MCP server entry point
│   ├─ analyzers/             # 🔍 Code analysis
│   │   ├─ __init__.py
│   │   └─ code_analyzer.py   # Multi-tool static analysis
│   ├─ generators/            # 🧪 Test generation
│   │   ├─ __init__.py
│   │   └─ test_generator.py  # AST-based test creation
│   └─ executors/             # ▶️ Test execution
│       ├─ __init__.py
│       └─ test_executor.py   # Test running & formatting
├─ pyproject.toml             # Project configuration
├─ README.md                  # This file
├─ test_installation.py       # Installation validator
├─ examples.py                # Usage examples
└─ requirements.txt           # Dependencies

{
  "mcpServers": {
    "neurodev-mcp": {
      "command": "/absolute/path/to/neurodev-mcp/.venv/bin/python",
      "args": ["-m", "neurodev_mcp.server"]
    }
  }
}

{
  "neurodev-mcp": {
    "command": "python",
    "args": ["-m", "neurodev_mcp.server"]
  }
}

# Using the module
python -m neurodev_mcp.server

# Or as a command (if installed)
neurodev-mcp

# Default STDIO transport
neurodev-mcp

# Or explicitly specify STDIO
neurodev-mcp --transport stdio

{
  "mcpServers": {
    "neurodev-mcp": {
      "command": "neurodev-mcp",
      "args": ["--transport", "stdio"]
    }
  }
}

# Run with SSE on default port (8000)
neurodev-mcp --transport sse

# Custom host and port
neurodev-mcp --transport sse --host 0.0.0.0 --port 3000

const sse = new EventSource('http://localhost:8000/sse');

sse.onmessage = (event) => {
  const data = JSON.parse(event.data);
  console.log('Received:', data);
};

// Send message
fetch('http://localhost:8000/messages', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({
    method: 'tools/call',
    params: {
      name: 'code_review',
      arguments: { code: 'def test(): pass', analyzers: ['pylint'] }
    }
  })
});

{
  "code": "def calculate(x):\n    return x * 2",
  "analyzers": ["pylint", "flake8", "mypy", "bandit", "radon", "ast"]
}

{
  "code": "def add(a: int, b: int) -> int:\n    return a + b",
  "module_name": "calculator",
  "save": false
}

{
  "test_code": "def test_add():\n    assert add(1, 2) == 3",
  "source_code": "def add(a, b):\n    return a + b",
  "timeout": 30
}

{
  "code": "def   messy(  x,y  ):\n        return x+y",
  "line_length": 88
}

You: "Review this code for issues and security problems"

[paste code]

AI: [Uses code_review tool]
    → Finds 3 style issues
    → Detects 1 security vulnerability
    → Suggests complexity improvements
    
You: "Fix those issues and show me the updated code"

AI: [Provides fixed code with explanations]

You: "Generate tests for this function and run them"

def divide(a: float, b: float) -> float:
    if b == 0:
        raise ValueError("Cannot divide by zero")
    return a / b

AI: [Uses generate_tests tool]
    → Creates 5 test cases
    → Includes edge cases (zero, negative numbers)
    → Tests exception handling
    
    [Uses run_tests tool]
    → 5/5 tests passing ✓
    → 100% code coverage
    → All edge cases handled

You: "Format this messy code"

def   calculate(  x,y,z  ):
        result=x+y+z
        if result>10:
                    return   True
        return False

AI: [Uses format_code tool]
    → Applies black formatting
    → Returns clean, PEP8-compliant code

def calculate(x, y, z):
    result = x + y + z
    if result > 10:
        return True
    return False

# Run installation tests
python test_installation.py

# Run examples
python examples.py

# Run pytest (if you add tests)
pytest

from neurodev_mcp import CodeAnalyzer, TestGenerator, TestExecutor
import asyncio

# Analyze code
code = "def hello(): print('world')"
result = asyncio.run(CodeAnalyzer.analyze_ast(code))

# Generate tests
tests = TestGenerator.generate_tests(code, "mymodule")

# Run tests
output = TestExecutor.run_tests(test_code, source_code)

# Reinstall the package
pip install -e .

# Verify installation
python -c "from neurodev_mcp import CodeAnalyzer; print('✓ OK')"

# Run installation tests
python test_installation.py