Chatgpt Interlocutor

An MCP server that gives Claude Code a ChatGPT second opinion. Cross-model adversarial review without leaving your terminal.

Why

When you're working in Claude Code, sometimes you want a second perspective — a different model's take on the same problem. Not because one is better, but because disagreement surfaces blind spots.

This server adds two tools to every Claude Code session:

• ask_chatgpt — Send a question to ChatGPT and get its response inline. Second opinions, alternative approaches, sanity checks.
• compare_approaches — Send the same prompt to both models and get a structured comparison. Specificity, depth, accuracy, voice.

Install

Prerequisites

You need an OpenAI API key.

Add to Claude Code

Add this to your ~/.claude.json under mcpServers:

{
  "mcpServers": {
    "chatgpt-interlocutor": {
      "command": "npx",
      "args": ["-y", "chatgpt-interlocutor"],
      "env": {
        "OPENAI_API_KEY": "sk-your-key-here"
      }
    }
  }
}

Restart Claude Code. You should see ask_chatgpt and compare_approaches in your available tools.

Or install globally

npm install -g chatgpt-interlocutor

Then configure with the direct path:

{
  "mcpServers": {
    "chatgpt-interlocutor": {
      "command": "chatgpt-interlocutor",
      "env": {
        "OPENAI_API_KEY": "sk-your-key-here"
      }
    }
  }
}

Tools

ask_chatgpt

Get a second opinion from ChatGPT.

Parameter	Type	Default	Description
prompt	string	required	The question or task to send
model	string	gpt-4o-mini	gpt-4o-mini, gpt-4o, or o3-mini
system	string	—	Optional system prompt for context
temperature	number	0.7	Creativity 0–2. Lower = more focused

compare_approaches

Benchmark Claude's output against ChatGPT's on the same task.

Parameter	Type	Default	Description
task_description	string	required	What both models are being asked to do
prompt	string	required	The prompt to send to ChatGPT
your_output	string	—	Claude's output for side-by-side comparison
model	string	gpt-4o-mini	Which ChatGPT model to use

When your_output is provided, the response includes a comparison framework:

• Specificity — Which is more concrete and actionable?
• Depth — Which goes deeper into the problem?
• Voice — Which sounds more human / less generic AI?
• Structure — Which is better organized?
• Accuracy — Which is more correct?
• Differentiation — Where do they diverge most?

Models

Model	Cost	Best for
gpt-4o-mini	Cheapest	Quick second opinions, brainstorming
gpt-4o	Mid	Deeper analysis, complex reasoning
o3-mini	Mid	Math, logic, structured reasoning

How it works

This is a Model Context Protocol server that runs over stdio. Claude Code launches it as a subprocess, sends tool calls, and gets responses back. Your prompts go to the OpenAI API using your own key — nothing is stored or proxied.

License

MIT