mockloop

MockLoop MCP is an AI-native API testing platform that runs as an MCP server and provides a suite of AI-driven prompts, scenario packs, and automated tooling to design, execute, and analyze API tests. The server exposes 5 AI prompts for intelligent scenario creation, 15 scenario resource packs for reusable test configurations, and 16 tools split across scenario management, test execution, and analysis. You can leverage global and agent context to build stateful test flows and perform comprehensive audit logging for compliance. To start using it, install the package, run the MCP server, and connect your MCP-enabled clients or tooling to the server endpoint to request scenario generation, deploy tests, and execute automated test plans. Explore the available prompts to generate testing strategies, configure scenarios, optimize load, simulate errors, and test security aspects, then deploy and execute them through the provided tooling for end-to-end testing and reporting.

Prerequisites:

• Python 3.8+ (or a compatible Python environment)
• Internet access to install packages from PyPI

Installation steps:

1. Create and activate a virtual environment (optional but recommended): python3 -m venv venv source venv/bin/activate # macOS/Linux venv\Scripts\activate.bat # Windows

2. Install the MockLoop MCP package from PyPI: pip install mockloop-mcp

3. Run the MCP server (examples): python -m mockloop_mcp

4. Verify the server is running by visiting the configured API endpoint or checking the console logs for startup messages.

If you prefer to install from source, clone the repository and install in editable mode: pip install -e .

Note: If you deploy via container or other environments, ensure Python is available and required dependencies are installed as defined in the project’s setup configuration.

Tips and common considerations:

• Ensure you have a valid API key or credentials if the server interacts with MockLoop services; configure these via environment variables (e.g., MOCKLOOP_API_KEY).
• SchemaPin validation is recommended to verify tool schemas; verify you are using releases from the official repository to avoid forks.
• The MCP server supports environment-specific endpoints; adjust MOCKLOOP_API_ENDPOINT accordingly for dev/staging/prod environments.
• If you encounter port conflicts or admin path issues, leverage the Dual-Port Architecture by configuring separate ports for the mocked API and admin interfaces as described in the docs.
• For troubleshooting, check startup logs for MCP Prompts and Tools initialization messages to confirm all components are loaded correctly.