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swagger-mcp

by danishjsheikh

swagger-mcp is a tool designed to scrape Swagger UI by extracting the `swagger.json` file and dynamically generating well-defined mcp tools at runtime. These tools can be utilized by the MCP client for further tool selection.

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What is swagger-mcp?

swagger-mcp is a tool that scrapes Swagger UI, extracts the swagger.json file, and dynamically generates MCP tools. These tools are designed to be used by an MCP client for tool selection and integration with LLMs.

How to use swagger-mcp?

To use swagger-mcp, install it using go install github.com/danishjsheikh/swagger-mcp@latest. Then, configure your MCP client (e.g., mcphost) to use swagger-mcp by adding it to the mcpServers configuration with the command swagger-mcp and the Swagger/doc.json URL as an argument. Ensure you have the necessary prerequisites, including an LLM API key and an MCP client.

Key features of swagger-mcp

  • Dynamic MCP tool generation from Swagger UI

  • Automated API integration with LLMs

  • Support for OpenAI, Claude, and Ollama models

  • Integration with MCP clients like mark3labs - mcphost

Use cases of swagger-mcp

  • Automating API integration with LLM-powered applications

  • Dynamically creating MCP tools for various APIs

  • Simplifying the process of integrating Swagger-defined APIs into MCP workflows

  • Enabling LLMs to interact with APIs based on their Swagger definitions

FAQ from swagger-mcp

What is an MCP?

MCP stands for Model Context Protocol. It's a framework for managing and interacting with different models and contexts.

What LLM models are supported?

The tool supports OpenAI, Claude, and Ollama models.

How do I integrate swagger-mcp with mcphost?

Include the provided configuration in your .mcp.json file, specifying the command and arguments for swagger-mcp.

What are the prerequisites for using swagger-mcp?

You need an LLM Model API Key (or a local LLM) and an MCP Client (like mark3labs - mcphost).

Where can I find a demo of swagger-mcp in action?

A demo video is available on LinkedIn, linked in the README file.