Intelligent Model Context Protocol (MCP) server for AI-assisted API development. Generate mock servers from OpenAPI specs with advanced logging, performance analytics, and server discovery. Optimized for AI development workflows with comprehensive testing insights and automated analysis.
Overview
What is MockLoop MCP?
MockLoop MCP is an AI-native testing platform designed for API development, utilizing the Intelligent Model Context Protocol (MCP) to generate mock servers from OpenAPI specifications. It offers advanced logging, performance analytics, and server discovery, optimized for AI development workflows.
How to use MockLoop MCP?
To use MockLoop MCP, install it via pip, configure it with your MCP client, and utilize its tools to generate mock servers and execute tests.
Key features of MockLoop MCP?
- AI-driven test generation with specialized prompts.
- Automated test execution with comprehensive tools.
- Stateful testing workflows with advanced context management.
- Enterprise-grade compliance and audit logging.
Use cases of MockLoop MCP?
- Generating mock APIs for testing.
- Conducting load and security tests on APIs.
- Analyzing performance metrics and generating reports.
FAQ from MockLoop MCP?
- Can MockLoop MCP be used for all types of APIs?
Yes, it supports REST, GraphQL, and gRPC APIs.
- Is MockLoop MCP free to use?
It is open-source and available for free on GitHub.
- What are the prerequisites for using MockLoop MCP?
You need Python 3.10+, pip, Docker, and an MCP-compatible client.