Retrieve and view all saved drafts for the current user, including keys, sequences, and preview content, to identify existing drafts before making updates.
MCP-ORTools integrates Google's OR-Tools constraint programming solver with Large Language Models through the MCP, enabling AI models to:
Submit and validate constraint models
Set model parameters
Solve constraint satisfaction and optimization problems
Retrieve and analyze solution
Automatically converts Swagger/OpenAPI specifications into dynamic MCP tools, enabling interaction with any REST API through natural language by loading specs from local files or URLs.
A standalone proxy that transforms any OpenAPI or Swagger-described REST API into an MCP server by mapping API operations to executable MCP tools. It enables AI clients to interact with existing web services through automated HTTP requests based on their official documentation.