Python Testing Tools MCP Server
An advanced Model Context Protocol (MCP) server that provides AI-powered Python testing tools. This project leverages both Google's Gemini AI and BAML (Boundary ML) to intelligently generate comprehensive unit tests and perform sophisticated fuzz testing on Python code.
Overview
Python Testing Tools MCP Server
An advanced Model Context Protocol (MCP) server that provides AI-powered Python testing tools. This project leverages both Google's Gemini AI and BAML (Boundary ML) to intelligently generate comprehensive unit tests and perform sophisticated fuzz testing on Python code.
Overview
This MCP server offers automated testing capabilities through three main tools:
- Intelligent Unit Test Generation - Automatically creates comprehensive test suites with proper edge cases, assertions, and error handling
- AI-Powered Fuzz Testing - Generates diverse, challenging inputs to test function robustness and discover potential crashes
- Advanced Coverage Testing - Generates comprehensive test suites designed to achieve maximum code coverage with intelligent branch, loop, and exception path analysis
The server uses a hybrid AI approach: BAML for structured test generation and Gemini for intelligent input generation, ensuring high-quality, reliable test outputs.
Key Features
- AI-Powered Unit Test Generation: Uses BAML with Gemini to generate comprehensive unittest suites covering normal cases, edge cases, and error conditions
- Intelligent Fuzz Testing: Leverages AI to generate diverse, challenging inputs that test function boundaries and error handling
- Advanced Coverage Testing: AST-based code analysis with AI-generated tests targeting specific coverage scenarios for maximum line and branch coverage
- Built-in Coverage Measurement: Integrates coverage.py library for real-time coverage reporting and analysis
- BAML Integration: Structured AI responses using BAML (Boundary ML) for consistent, parseable test generation
- FastMCP Framework: Built on FastMCP for efficient MCP server implementation
- Robust Error Handling: Graceful fallbacks and detailed error reporting throughout the testing pipeline
- Modular Architecture: Clean separation between tools, utilities, and AI clients for easy extension
- Advanced Code Analysis: Uses Python AST parsing for accurate function extraction, branch detection, and control flow analysis
Server Config
{
"/path/to/your/project": {
"mcpServers": {
"python_testing_tools": {
"type": "stdio",
"command": "uv",
"args": [
"run",
"--with",
"fastmcp",
"fastmcp",
"run",
"/path/to/your/project/python_testing_mcp_server.py"
],
"env": {
"GEMINI_API_KEY": "your-api-key-here"
}
}
}
}
}Project Info
Created At
10 months agoUpdated At
10 months agoAuthor Name
jazzberry-aiStar
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