ChatGPT MCP Server

A local MCP (Model Context Protocol) server that gives Claude Code access to specialized ChatGPT review and advisory tools.

The server provides structured second-opinion workflows for:

  • General questions and alternative viewpoints
  • Implementation plan reviews
  • Code reviews
  • Debugging investigations
  • Architecture reviews

Claude Code remains the primary coding agent. ChatGPT acts only as an advisor and reviewer.


Purpose

This project combines the strengths of both models:

  • Claude Code performs implementation, editing, refactoring, testing, and repository operations.
  • ChatGPT provides independent analysis, review, risk assessment, debugging assistance, and architectural feedback.

The goal is to improve decision quality without introducing autonomous behaviour.


Non-Goals

The server must not:

  • Modify files
  • Run shell commands
  • Access Git automatically
  • Deploy anything
  • Send entire repositories by default
  • Send secrets
  • Make autonomous decisions

ChatGPT only returns analysis and recommendations.


Architecture

Claude Code
    ↓
MCP Tool
    ↓
Input Validation
    ↓
Context Budget Enforcement
    ↓
Prompt Builder
    ↓
Provider Factory (createChatProvider)
    ↓
OpenAI Provider → OpenAI Responses API
    ↓
Advisory Response

The provider layer is configurable via CHATGPT_MCP_PROVIDER env var. Currently only "openai" is supported, but the factory pattern enables future providers without touching tool handlers.

All responses are advisory only.


Available MCP Tools

Tool Purpose
ask_chatgpt General second-opinion questions, alternatives, risks, trade-offs, and clarification.
review_plan Reviews implementation plans for missing steps, sequencing issues, unsafe assumptions, scope creep, and test gaps.
review_code Reviews code snippets, patches, and diffs for correctness, bugs, maintainability, security concerns, and testing opportunities.
debug_issue Analyses errors, logs, failed tests, and stack traces to identify likely root causes and propose safe investigation steps.
architecture_review Reviews architecture decisions, system design, trade-offs, maintainability, operational risk, vendor lock-in, and future evolution paths.

Features

OpenAI Integration

  • OpenAI Responses API
  • Configurable model selection
  • Dependency-injected design for testability
  • Structured error handling
  • Safe error messages without secret leakage

Prompt System

  • Shared base prompt layer
  • Tool-specific prompt builders
  • Consistent advisory behaviour
  • Structured response guidance

Input Protection

  • Zod-based validation
  • Context budget enforcement
  • File size limits
  • Log size limits
  • Secret redaction utilities

MCP Integration

  • MCP stdio server
  • Tool discovery via tools/list
  • Structured tool responses
  • Claude Code integration

Testing

  • 523+ automated tests
  • Unit-tested utilities
  • Prompt builder coverage
  • OpenAI integration coverage
  • Tool handler orchestration coverage
  • MCP registration verification

Requirements

  • Node.js 20+
  • OpenAI API key
  • Claude Code (or another MCP-compatible client)

Installation

Install dependencies:

npm install

Set your OpenAI API key:

export OPENAI_API_KEY=sk-your-key

Optional environment variables:

export OPENAI_MODEL=gpt-5.1
export OPENAI_TEMPERATURE=0.2

Running Tests

npm test

Running the MCP Server

Start the stdio MCP server:

npm start

The server communicates over stdin/stdout and is intended to be launched by an MCP client rather than directly by users.


Claude Code Configuration

Configure Claude Code to discover the MCP server.

Create either:

  • Global configuration: ~/.claude/settings.json
  • Project-local configuration: .claude/settings.local.json

Example:

{
  "mcpServers": {
    "chatgpt-mcp": {
      "command": "npm",
      "args": ["start"]
    }
  }
}

After opening the project in Claude Code, the server should be automatically discovered and the five MCP tools should become available.


Current Status

MVP Complete

Implemented:

  • OpenAI Responses API integration
  • Shared validation and safety utilities
  • Context budget management
  • Five prompt builders
  • Five tool handlers
  • MCP stdio server
  • Registration of all five MCP tools
  • Claude Code integration documentation
  • Comprehensive automated test suite (523+ tests)

Next Steps

Planned future work includes:

  • Real-world workflow validation
  • Prompt refinements
  • Additional context-loading features
  • Improved operational diagnostics
  • Production hardening

Development Philosophy

Keep the system simple.

  • Prefer local-first solutions
  • Minimise moving parts
  • Avoid unnecessary abstractions
  • Favour small, testable modules
  • Keep ChatGPT advisory-only
  • Keep Claude Code in control

The objective is not autonomous development. The objective is better engineering decisions through independent review.

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