OpenAI MCP Server

MCP server providing comprehensive access to OpenAI's API capabilities.

Features

Core Capabilities

• Chat Completions - Generate responses using GPT-4o, GPT-4, and GPT-3.5 models

• Embeddings - Create vector embeddings for semantic search and similarity

• Image Generation - Generate images with DALL-E 3 and DALL-E 2

• Text-to-Speech - Convert text to natural-sounding speech

• Speech-to-Text - Transcribe audio using Whisper

• Vision Analysis - Analyze images with GPT-4 Vision

• Content Moderation - Check content against usage policies

• Model Management - List and explore available models

Installation

1. Clone this repository

2. Install dependencies:

3. Set up your environment variables:

Configuration

Get Your OpenAI API Key

1. Go to https://platform.openai.com/api-keys

2. Sign in or create an account

3. Click "Create new secret key"

4. Copy the key and add it to your .env file

Running the Server

HTTP Mode (Recommended for NimbleBrain)

Start the server:

The server will be available at http://localhost:8000

Claude Desktop Configuration

Add to your claude_desktop_config.json:

HTTP Configuration:

Alternative - Direct Python (stdio):

If you need stdio mode instead of HTTP, you can run directly:

Windows (%APPDATA%\Claude\claude_desktop_config.json):

macOS (~/Library/Application Support/Claude/claude_desktop_config.json):

Available Tools

chat_completion

Generate conversational responses using OpenAI's chat models.

Parameters:

• messages (required): List of message objects with 'role' and 'content'

• model: Model name (default: "gpt-4o-mini")

• temperature: Creativity level 0-2 (default: 1.0)

• max_tokens: Maximum response length

• response_format: Optional "json_object" for JSON responses

Example:

create_embedding

Generate vector embeddings for text.

Parameters:

• text (required): Text to embed

• model: Embedding model (default: "text-embedding-3-small")

Use Cases:

• Semantic search

• Document similarity

• Clustering and classification

• Recommendation systems

generate_image

Create images from text descriptions using DALL-E.

Parameters:

• prompt (required): Description of desired image

• model: "dall-e-3" or "dall-e-2" (default: "dall-e-3")

• size: Image dimensions (1024x1024, 1792x1024, 1024x1792)

• quality: "standard" or "hd" (DALL-E 3 only)

• n: Number of images (1-10, only 1 for DALL-E 3)

text_to_speech

Convert text to natural-sounding audio.

Parameters:

• text (required): Text to convert

• voice: alloy, echo, fable, onyx, nova, shimmer (default: "alloy")

• model: "tts-1" or "tts-1-hd" (default: "tts-1")

• speed: Speech rate 0.25-4.0 (default: 1.0)

Returns: Base64 encoded MP3 audio

transcribe_audio

Transcribe audio to text using Whisper.

Parameters:

• audio_file_base64 (required): Base64 encoded audio file

• model: "whisper-1"

• language: Optional language code (auto-detected if not provided)

• response_format: json, text, srt, vtt, verbose_json

analyze_image

Analyze images using GPT-4 Vision.

Parameters:

• image_url (required): URL of image to analyze

• prompt: Question about the image (default: "What's in this image?")

• model: Vision model (default: "gpt-4o-mini")

• max_tokens: Maximum response length

moderate_content

Check if content violates OpenAI's usage policies.

Parameters:

• text (required): Content to moderate

• model: "text-moderation-latest" or "text-moderation-stable"

Returns: Flags and scores for various content categories

list_models

Get all available OpenAI models with metadata.

Usage Examples

Chat Conversation

Generate Marketing Image

Create Product Description Embeddings

Transcribe Meeting Recording

Model Recommendations

Chat Models

• gpt-4o: Best overall, multimodal, fast

• gpt-4o-mini: Cost-effective, very fast

• gpt-4-turbo: High intelligence, good for complex tasks

• gpt-3.5-turbo: Fast and affordable for simple tasks

Embedding Models

• text-embedding-3-small: Best price/performance (1536 dimensions)

• text-embedding-3-large: Highest quality (3072 dimensions)

Image Models

• dall-e-3: Higher quality, better prompt following

• dall-e-2: More images per request, lower cost

Error Handling

The server includes comprehensive error handling for:

• Invalid API keys

• Rate limiting

• Invalid model names

• Malformed requests

• Network timeouts

Rate Limits

OpenAI enforces rate limits based on your account tier:

• Free tier: Limited requests per minute

• Pay-as-you-go: Higher limits based on usage

• Enterprise: Custom limits

Check your limits at: https://platform.openai.com/account/limits

Pricing

Approximate costs (check OpenAI pricing page for current rates):

• GPT-4o: ~$2.50 per 1M input tokens

• GPT-4o-mini: ~$0.15 per 1M input tokens

• Text Embeddings: ~$0.02 per 1M tokens

• DALL-E 3: ~$0.04 per standard image

• Whisper: ~$0.006 per minute

Security Notes

• Never commit your API key to version control

• Use environment variables for sensitive data

• Rotate API keys regularly

• Monitor usage on OpenAI dashboard

• Set spending limits in your OpenAI account

Troubleshooting

"Invalid API Key" Error

• Verify key is correct in .env file

• Ensure no extra spaces or quotes

• Check key is active at https://platform.openai.com/api-keys

Rate Limit Errors

• Implement exponential backoff

• Upgrade account tier if needed

• Reduce request frequency

Timeout Errors

• Increase timeout in httpx client

• Check network connectivity

• Try with smaller requests

Resources

• OpenAI API Documentation

• OpenAI Pricing

• OpenAI Cookbook

• Model Context Protocol

License

MIT License - feel free to use in your projects!