MCP Python Function Generator Server
by Neshri
This MCP server exposes a tool to generate Python function code from a natural language description. It supports optional human-provided testing to validate the generated code.
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What is MCP Python Function Generator Server?
The MCP Python Function Generator Server is a tool that generates Python function code based on a natural language description provided by the user. It can optionally use human-validated test cases to ensure the generated code meets specific requirements.
How to use MCP Python Function Generator Server?
- Install uv and clone the repository. 2. Run the setup script (setup.bat or setup.sh). 3. Configure your MCP client (e.g., Claude Desktop) with the command and arguments provided by the setup script, ensuring the path is absolute and backslashes are escaped in Windows. 4. Restart your MCP client. 5. Call the
create_python_functiontool with arequirement(description of the function) and optionaltest_cases.
Key features of MCP Python Function Generator Server
Generates Python function code from natural language descriptions
Supports human-validated test cases for code verification
Easy setup using uv package manager
Validates code syntax and function definition
Returns the generated function specification, code, and test results
Use cases of MCP Python Function Generator Server
Rapid prototyping of Python functions
Generating boilerplate code for specific tasks
Automating the creation of simple utility functions
Validating AI-generated code with human-provided test cases
FAQ from MCP Python Function Generator Server
What is MCP?
What is MCP?
MCP likely refers to a Message Communication Protocol or similar framework for inter-process communication.
What are the prerequisites for using this server?
What are the prerequisites for using this server?
You need to have uv installed and available in your system's PATH.
How do I configure my MCP client?
How do I configure my MCP client?
Copy the command and args array printed by the setup script into your MCP client's configuration file.
What is the structure of the test_cases argument?
What is the structure of the test_cases argument?
It is an array of objects, where each object has 'inputs' (a dictionary of parameter names and values) and 'expected' (the expected output value).
Can I use AI-generated test cases?
Can I use AI-generated test cases?
No, the test_cases argument is intended only for tests written or validated by a human. Do not use AI-generated test cases.