Overview

Model Context Protocol (MCP) is a standardization of how AI assistants interact with APIs, and ReadMe is bringing this capability to your developer hub. With MCP servers, you can convert your API documentation into a structured, resource that AI assistants can understand and interact with programmatically.

Key Features

OpenAPI Integration: Generate an MCP server from your existing OpenAPI specification.
AI assistants can connect to your MCP server to:
- Read and understand your OpenAPI spec.
- Execute API calls.
- Search docs with Owlbot.
AI Tools Included:
- OpenAPI Tools:
  - execute-request-body - Make API calls directly from your specification
  - get-endpoint - Pull in detailed endpoint information on demand
  - get-request-body - Access structured request parameters
  - get-response-schema - Understand what your API returns
  - list-endpoints - Browse all available API endpoints
  - list-security-schemes - Access authentication requirements
  - search-schema - Find exactly what you need in your API spec
  - get-code-snippet - Example code snippets in your preferred language to interact with your endpoint.
- Documentation Search:
  - search-documentation - Leverage Owlbot to search your entire knowledge base

How It Works

We create a dedicated MCP server that connects to your OpenAPI specification and Owlbot search functionality. This creates a bridge between your API documentation and AI assistants, making your API instantly more accessible and understandable to AI tools.

Getting Started with MCP

Choose how you’d like to start working with MCP:

Auto-Generate Your Own MCP Server: Every ReadMe project automatically includes a fully configured MCP server. Simply enable MCP to connect your API documentation to AI tools.
Use ReadMe's MCP Server: With ReadMe's MCP server, you can do everything you normally would in ReadMe, like adding and editing pages, directly through our API.