6 posts tagged with "MCP"

You want your API to be instantly usable inside AI assistants like ChatGPT, and Web UIs. The OpenAI UI SDK plus the Model Context Protocol (MCP) lets you expose your API as structured tools that large language models can call directly.

For years, OpenAPI (OAS) has been the cornerstone of how we describe, document, and integrate APIs. It standardized how systems talk to each other — and in many ways, it made the modern internet possible.

So when the Model Context Protocol (MCP) appeared, some developers were skeptical. "Another spec?" they asked. "Why do we need this when we already have OAS?"

This guide demonstrates how to use the OpenAI Response API to integrate with the Model Context Protocol (MCP) for seamless, AI-driven API interactions. You will learn how to generate a REST API specification with Postman's AI Agent, deploy it as an MCP server using HAPI Server, and connect it through OpenAI's Response API for testing.

An evolution of tool calling with MCP, thanks to OpenAI's latest SDK updates.

Step-by-step, I'll guide you through setting up an MCP server, integrating it with the OpenAI SDK, and running a complete example that showcases dynamic tool calling. By the end of this post, you'll be equipped to leverage MCP in your own OpenAI-powered applications.

Prompt injection is a critical security risk for any system using large language models (LLMs), including those built with Model Context Protocol (MCP). You must understand how prompt injection works, why MCP cannot prevent it, and what steps you should take to protect your users and applications (MCP Clients).

🚨 "OpenAPI Specification (OAS) v4 is out" - That I wish, this is the kind of headline I would expect to see soon, because OAS can easily be extended to enable RESTful APIs work seamlessly with AI.

By the end of this article, you'll know how to let any LLM call your REST tools automatically using OAS.