OpenAI Multi-Model MCP Server

A Model Context Protocol (MCP) server that enables Claude Code to interact with OpenAI's GPT-5 and GPT-5-mini models.

Features

• Multi-model support: Choose between GPT-5 and GPT-5-mini per request
• Advanced parameters: Support for reasoning effort, verbosity control, and system instructions
• Type-safe: Built with TypeScript and Zod validation
• Error handling: Comprehensive error handling with structured responses
• MCP compliant: Full compatibility with MCP specification

Quick Start

Claude Code Configuration

Add to your Claude Code MCP configuration (typically in ~/.claude.json):

Option 1 - From GitHub (Recommended):

{
  "mcpServers": {
    "openai-multi": {
      "command": "npx",
      "args": ["-y", "github:vladnicula/vlads-openai-mcp-server"],
      "env": {
        "OPENAI_API_KEY": "sk-your-openai-api-key-here"
      }
    }
  }
}

Option 2 - Local installation:

{
  "mcpServers": {
    "openai-multi": {
      "command": "node",
      "args": ["/path/to/vlads-openai-mcp-server/build/index.js"],
      "env": {
        "OPENAI_API_KEY": "sk-your-openai-api-key-here"
      }
    }
  }
}

Note: Adding this configuration to the root mcpServers object will make it available in all instances of Claude Code.

Setup

If you wanna build this on your local machine, patch thing up, extend things. PRs are welcome btw.

Prerequisites

• Node.js 18+
• OpenAI API key

Installation

1. Clone or navigate to the project directory:

   cd /path/to/vlads-openai-mcp-server
   

2. Install dependencies:

   npm install
   

3. Create environment configuration (for local testing only):

   cp .env.example .env
   # Edit .env and add your OpenAI API key - only needed for MCP Inspector testing
   

4. Build the project:

   npm run build
   

Configuration

Environment Variables

Create a .env file with:

OPENAI_API_KEY=sk-your-openai-api-key-here

Usage

Available Tools

openai_chat

Chat with OpenAI models including GPT-5 and GPT-5-mini.

Parameters:

• model (required): "gpt-5" or "gpt-5-mini"
• input (required): String text input for the model
• instructions (optional): System-level instructions
• reasoning (optional): Object with effort property ("minimal", "low", "medium", "high")
• text (optional): Object with verbosity property ("low", "medium", "high")
• max_tokens (optional): Maximum tokens in response

Example:

// GPT-5 for complex tasks
await openai_chat({
  model: "gpt-5",
  input: "Explain quantum computing in detail",
  instructions: "You are a helpful physics tutor",
  reasoning: {
    effort: "high"
  },
  text: {
    verbosity: "high"
  }
});

// GPT-5-mini for quick responses
await openai_chat({
  model: "gpt-5-mini",
  input: "What's the weather like?",
  reasoning: {
    effort: "minimal"
  }
});

Development

Scripts

• npm run dev - Run in development mode with hot reload
• npm run build - Build for production
• npm run start - Run built version
• npm run inspector - Test with MCP Inspector
• npm run test - Run tests

Testing

Use the MCP Inspector to test the server:

npm run inspector

This will start the MCP Inspector where you can:

1. Test tool definitions
2. Try different parameter combinations
3. Verify error handling

Project Structure

src/
├── index.ts          # Main server entry point
├── client.ts         # OpenAI API client wrapper
├── tools/
│   ├── index.ts      # Tool registry
│   └── chat.ts       # Chat tool implementation
├── schemas/
│   └── index.ts      # Zod validation schemas
└── utils/
    └── env.ts        # Environment validation

Model Comparison

Feature	GPT-5	GPT-5-mini
Performance	Best	Fast
Cost	Higher	Lower
Context Window	400k tokens	400k tokens
Verbosity Control	Yes	No
Multi-modal	Yes	Yes

Error Handling

The server provides structured error responses:

• Validation errors: Invalid input parameters
• API errors: OpenAI API issues (rate limits, auth, etc.)
• Network errors: Connectivity problems
• Unexpected errors: Any other failures

All errors include helpful messages and, where applicable, error codes.

Troubleshooting

Common Issues

1. Missing API Key

   Missing required environment variable: OPENAI_API_KEY
   

   Solution: Set your OpenAI API key in the environment

2. Model Not Found

   OpenAI API Error: The model 'gpt-5' does not exist
   

   Solution: Ensure you have access to GPT-5 models in your OpenAI account

3. Rate Limits

   OpenAI API Error: Rate limit exceeded
   

   Solution: Wait and retry, or upgrade your OpenAI plan

Debug Mode

The server logs detailed information to stderr:

• Request details
• Response metadata
• Error information

License

MIT

Contributing

1. Follow the existing code style
2. Add tests for new features
3. Update documentation
4. Ensure all tests pass