OpenAI MCP Server

A Model Context Protocol (MCP) server implementation for the OpenAI API. This server provides a standardized interface between Augment and OpenAI's language models using the official MCP SDK.

What is MCP?

The Model Context Protocol (MCP) is a standardized API specification that provides a unified way to interact with various large language models (LLMs). It allows applications like Augment to work with different LLM providers through a consistent interface.

MCP acts as a "universal adapter" for LLMs - it translates application requests into the specific format each LLM provider requires.

Features

- 🔄 Uses the official MCP SDK for compatibility
- Secure API key management
- 📊 Support for chat completions
- 📋 Model listing
- 🧠 Embedding generation
- ⚠️ Proper error handling and logging

Prerequisites

- Node.js (v16 or higher)
- npm or yarn
- OpenAI API key

Installation

1. Clone this repository or copy the files to your project directory
2. Install dependencies:

npm install

3. Create a .env file based on the .env.example provided:

cp .env.example .env

4. Add your OpenAI API key to the .env file:

OPENAI_API_KEY=your_openai_api_key_here

Running the Server

Start the server with:

npm start

For development with auto-restart on file changes:

npm run dev

Using with Augment

To use this MCP server with Augment, add the following to your Augment settings.json file:

"augment.advanced": {
    "mcpServers": [
        {
            "name": "openai-mcp",
            "command": "node",
            "args": ["/path/to/openai-mcp-server.js"],
            "env": {
                "OPENAI_API_KEY": "your_openai_api_key_here",
                "DEBUG": "true"
            }
        }
    ]
}

Replace /path/to/openai-mcp-server.js with the actual path to the server file on your system.

Available Tools

This MCP server provides the following tools to Augment:

1. List Models

Lists all available OpenAI models.

2. Chat Completion

Generates responses using OpenAI's chat completion API. Supports parameters like:
- model: The model to use (e.g., gpt-3.5-turbo, gpt-4)
- messages: Array of conversation messages
- temperature: Controls randomness (0-1)
- max_tokens: Maximum number of tokens to generate

3. Create Embedding

Generates embeddings for text using OpenAI's embedding API. Supports parameters like:
- model: The model to use (e.g., text-embedding-ada-002)
- input: The text to embed (string or array of strings)

Testing

A sample client is provided in client-example.js to test your MCP server. Run it with:

node client-example.js

Understanding the Code

The server consists of several key components:

1. MCP SDK Integration: Uses the official MCP SDK for standardized communication
2. Tool Handlers: Implements handlers for each supported tool
3. OpenAI API Integration: Communicates with OpenAI's API
4. Error Handling: Provides consistent error responses
5. Logging: Logs operations for debugging

Potential Improvements

See mcp-server-improvement-suggestions.md for a list of potential improvements that could be made to this implementation.

License

MIT