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Mockloop MCP

Mockloop MCP: Intelligent Model Context Protocol Server

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Welcome to the Mockloop MCP repository! This project offers an Intelligent Model Context Protocol (MCP) server tailored for AI-assisted API development. With our tool, you can generate mock servers directly from OpenAPI specifications. The server comes equipped with advanced logging, performance analytics, and server discovery features, making it a robust solution for your development needs.

Table of Contents

  1. Features
  2. Installation
  3. Usage
  4. API Documentation
  5. Contributing
  6. License
  7. Contact

Features

  • Mock Server Generation: Easily create mock servers from OpenAPI specs.
  • Advanced Logging: Keep track of requests and responses for better debugging.
  • Performance Analytics: Analyze server performance with built-in metrics.
  • Server Discovery: Automatically discover available mock servers in your environment.
  • Optimized for AI Workflows: Designed to support AI development with comprehensive testing insights and automated analysis.

Installation

To get started with Mockloop MCP, you need to download the latest release. You can find it here. Download the appropriate file for your operating system, and follow the instructions below to set it up.

Prerequisites

  • Node.js: Ensure you have Node.js installed on your machine. You can download it from nodejs.org.
  • OpenAPI Spec: Have your OpenAPI specification ready to generate the mock server.

Steps to Install

  1. Download the latest release from here.
  2. Unzip the downloaded file.
  3. Open your terminal or command prompt.
  4. Navigate to the unzipped folder.
  5. Run the following command to install dependencies:
    npm install
  6. Start the server:
    npm start

Now your Mockloop MCP server is up and running!

Usage

Generating a Mock Server

To generate a mock server, you need to have your OpenAPI specification file ready. The following command will help you create a mock server from your OpenAPI spec:

npm run generate -- path/to/your/openapi-spec.yaml

Replace path/to/your/openapi-spec.yaml with the actual path to your OpenAPI specification file.

Accessing the Mock Server

Once the server is running, you can access it at http://localhost:3000. You can make requests to your mock endpoints just like you would with a real API.

Logging and Analytics

The server logs all requests and responses. You can view the logs in your terminal. Additionally, performance analytics are available to help you understand how your mock server is performing.

Server Discovery

Mockloop MCP supports server discovery. If you have multiple mock servers running, you can use the discovery feature to find and connect to them easily.

API Documentation

For detailed API documentation, please refer to the API Documentation. This document outlines all available endpoints, request/response formats, and example use cases.

Contributing

We welcome contributions to Mockloop MCP! If you have suggestions or improvements, please follow these steps:

  1. Fork the repository.
  2. Create a new branch for your feature or bug fix.
  3. Make your changes and commit them with clear messages.
  4. Push your branch to your forked repository.
  5. Create a pull request to the main repository.

Please ensure that your code adheres to our coding standards and includes appropriate tests.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Contact

For any inquiries or support, feel free to reach out:

Thank you for checking out Mockloop MCP! We hope it enhances your API development workflow. For updates and releases, always refer to the Releases section.

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security - not tested
A
license - permissive license
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quality - not tested

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

An Intelligent Model Context Protocol server that generates mock servers from OpenAPI specifications, featuring advanced logging, performance analytics, and server discovery for AI-assisted API development.

  1. Table of Contents
    1. Features
      1. Installation
        1. Prerequisites
        2. Steps to Install
      2. Usage
        1. Generating a Mock Server
        2. Accessing the Mock Server
        3. Logging and Analytics
        4. Server Discovery
      3. API Documentation
        1. Contributing
          1. License
            1. Contact

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