Overview
What is MCP?
The Model Context Protocol (MCP) is an open protocol designed to connect AI agents to the source of their system or data, thereby reducing friction between context and the AI. This project provides a server for running end-to-end (E2E) tests to automate the validation of AI-generated code.
How to use MCP?
To use the MCP server, you need to set up your development environment by creating a virtual environment, installing the required packages, and adding your LLM API key. You can then run the MCP inspector tool to debug your setup.
Key features of MCP?
- Automates the validation of AI-generated code through E2E tests.
- Integrates with various AI agents, including OpenAI.
- Provides a debugging tool for inspecting the MCP server.
Use cases of MCP?
- Validating AI-generated code in real-time.
- Enhancing the "Vibe Coding" workflow in AI IDEs like Cursor or Windsurf.
- Facilitating seamless integration between AI agents and data sources.
FAQ from MCP?
- What are the prerequisites for using MCP?
You need Python 3.11 or higher and an LLM provider like OpenAI.
- Is there a specific AI agent I must use?
No, you can use any AI you prefer as long as it supports the MCP protocol.
- How do I debug issues with MCP?
You can run the MCP inspector tool using the command provided in the setup instructions.