Python CLI Tool for Generating MCP Servers from API Specs
Generates an MCP server using Anthropic's SDK given input as OpenAPI or GraphQL specs.
What is Python CLI Tool for Generating MCP Servers from API Specs?
What is MCP? MCP is a Python CLI tool designed to generate Model Context Protocol (MCP) servers from API specifications such as OpenAPI or GraphQL. It automates the creation of a fully functional server project that adheres to best practices and integrates with Anthropic's MCP SDK. How to use MCP? To use MCP, provide an API specification file (in YAML or JSON for OpenAPI or SDL/IDL for GraphQL) and a JSON configuration file that defines generation options. Run the CLI tool, and it will generate the server project in the specified programming language (Python, TypeScript, Kotlin, or Rust). Key features of MCP? Accepts OpenAPI or GraphQL specifications and auto-detects the type. Generates an MCP server in the user-specified language with cleanly structured output. Implements configurable authentication middleware and privacy/security measures. Provides a structured README for installation, usage, and customization. Use cases of MCP? Quickly exposing data or services through an MCP server. Automating the creation of server projects for various programming languages. Ensuring compliance with security and privacy standards in API development. FAQ from MCP? Can MCP generate servers for all programming languages? Currently, MCP supports Python, TypeScript, Kotlin, and Rust. Is MCP free to use? Yes! MCP is open-source and free to use. How does MCP handle security and privacy? MCP includes options for authentication, data redaction, and secure headers to ensure compliance with best practices.
As an MCP (Model Context Protocol) server, Python CLI Tool for Generating MCP Servers from API Specs enables AI agents to communicate effectively through standardized interfaces. The Model Context Protocol simplifies integration between different AI models and agent systems.
How to use Python CLI Tool for Generating MCP Servers from API Specs
To use MCP, provide an API specification file (in YAML or JSON for OpenAPI or SDL/IDL for GraphQL) and a JSON configuration file that defines generation options. Run the CLI tool, and it will generate the server project in the specified programming language (Python, TypeScript, Kotlin, or Rust). Key features of MCP? Accepts OpenAPI or GraphQL specifications and auto-detects the type. Generates an MCP server in the user-specified language with cleanly structured output. Implements configurable authentication middleware and privacy/security measures. Provides a structured README for installation, usage, and customization. Use cases of MCP? Quickly exposing data or services through an MCP server. Automating the creation of server projects for various programming languages. Ensuring compliance with security and privacy standards in API development. FAQ from MCP? Can MCP generate servers for all programming languages? Currently, MCP supports Python, TypeScript, Kotlin, and Rust. Is MCP free to use? Yes! MCP is open-source and free to use. How does MCP handle security and privacy? MCP includes options for authentication, data redaction, and secure headers to ensure compliance with best practices.
Learn how to integrate this MCP server with your AI agents and leverage the Model Context Protocol for enhanced capabilities.
Use Cases for this MCP Server
- No use cases specified.
MCP servers like Python CLI Tool for Generating MCP Servers from API Specs can be used with various AI models including Claude and other language models to extend their capabilities through the Model Context Protocol.
About Model Context Protocol (MCP)
The Model Context Protocol (MCP) is a standardized way for AI agents to communicate with various services and tools. MCP servers like Python CLI Tool for Generating MCP Servers from API Specs provide specific capabilities that can be accessed through a consistent interface, making it easier to build powerful AI applications with complex workflows.
Browse the MCP Directory to discover more servers and clients that can enhance your AI agents' capabilities.