Server that ingests Swagger/OpenAPI specifications and Postman collections, providing just 4 strategic tools that allow AI agents to dynamically discover and interact with APIs instead of generating hundreds of individual tools.
A lightweight server implementation that exposes Python functions as discoverable tools via HTTP using the Machine-to-Machine Communication Protocol (MCP). Enables remote execution of Python functions through a JSON-RPC interface with async support and type safety.
Enables building agent-ready APIs that expose tools as both HTTP and MCP endpoints from a single server definition, with automatic OpenAPI, discovery docs, and interactive API reference.
A Flask-based server that implements Model Context Protocol to enhance LLMs with external tool capabilities via natural language, allowing tools like weather lookup and calculations to be invoked directly in the model's text output.