3 posts tagged with "ChatGPT"

MCP Apps look simple in the spec. Your tool returns HTML, the host renders it in an iframe, the user sees a dashboard instead of a wall of JSON. Build one app, it works everywhere.

In practice, I've shipped MCP Apps to both ChatGPT and Claude over the past few months and learned that "works everywhere" requires handling a surprising number of sharp edges — iframe sandboxing, data format differences, a picky initialization handshake, and an interactive tool-calling pattern that's barely documented anywhere.

Here's everything I've learned, with the exact code for each one.

When OpenAI integrated support for Anthropic's Model Context Protocol (MCP) into ChatGPT's deep research feature, they documented something elegant: a two-tool pattern that gives AI agents a consistent way to engage with any data source. If your MCP server implements search and fetch with their specific signatures, ChatGPT knows exactly how to explore your data without custom integration code.

Both tools accept only a single string parameter. That constraint isn't a limitation—it's what makes the pattern universal.

OpenAI just made it clear: if you want your MCP server to work with ChatGPT's deep research capabilities, it needs to implement two specific tools: search and fetch.

This isn't optional. It's the protocol standard that enables ChatGPT to discover and retrieve information from external data sources. And if you're using MCPBundles, you already have it.