Openapi MCP Server
O

Openapi MCP Server

This project is an OpenAPI MCP server used to provide pre - configured REST API context for LLMs, enabling LLMs to interact with REST APIs through prompts.
2.5 points
7.4K

What is the OpenAPI MCP Server?

The MCP (Model Context Protocol) server is a middleware that provides context interaction capabilities for large language models (LLMs) through pre - configured REST APIs. With this service, you can directly let the LLM perform API calls through natural language prompts.

How to use the OpenAPI MCP Server?

Simply install the Python package, configure the API endpoint information, and then you can start the service and integrate it with the LLM. It supports direct calls from platforms such as Claude Desktop.

Applicable scenarios

Suitable for scenarios where AI assistants need to access enterprise API systems, such as customer service automation, data query, business process triggering, etc.

Main features

API interaction proxy
Serves as a bridge between the LLM and REST APIs, converting natural language into API calls
Multi - protocol support
Supports HTTP method calls of GET/PUT/POST/PATCH
Access control
Controls accessible API endpoints through a whitelist/blacklist mechanism
Advantages
Allows LLMs to access APIs without writing code
Supports the standard OpenAPI specification, with strong compatibility
A flexible access control mechanism ensures security
Limitations
Currently only supports the HTTP protocol
Requires pre - configuration of API specification documents
Some complex APIs may require additional parameter processing

How to use

Install the service
Install the Python package via pip
Create a configuration file
Create a.env file in the project directory and configure the basic API information
Start the service
Run the service using the uv tool

Usage examples

Pet store query
Query pet information with a specific status
Update pet information
Modify the detailed information of an existing pet

Frequently Asked Questions

Do I need to deploy the API service myself?
Which LLM platforms are supported?
How to ensure the security of API calls?

Related resources

GitHub repository
Project source code and documentation
Example configuration file
Example of the.env configuration file
Introduction to the UV tool
Tutorial on using the UV tool

Installation

Copy the following command to your Client for configuration
Note: Your key is sensitive information, do not share it with anyone.

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