The OpenAIMCP server provides access to OpenAI's APIs through AceDataCloud, enabling text, image, audio, and embedding operations.
Chat Completions — Generate conversational responses with models like GPT-4, GPT-4o, GPT-5, and o-series (o1, o3, o4-mini), controlling temperature, max tokens, reasoning effort, and service tier.
Responses API — Access extended model variants (e.g., dated releases like o3-2025-04-16, search-preview) with optional background/async processing.
Image Generation — Create AI images from text using DALL·E 3, gpt-image-1, nano-banana, etc., with custom size, quality, output format, background transparency, and async callback workflows.
Image Editing — Modify existing images via URL with AI, controlling fidelity, size, quality, and format.
Text Embeddings — Convert text into vectors using text-embedding-3-small, text-embedding-3-large, or text-embedding-ada-002 for semantic search and similarity.
Audio — Text-to-speech and audio transcription from URLs using Whisper or GPT-Transcribe models.
Async Task Management — Retrieve individual image tasks or list/filter tasks (by ID, trace ID, etc.) created via callback-based asynchronous requests.
Model Discovery — List available chat, image, and embedding models.
Usage Guide — Access a comprehensive in-server guide with examples and best practices.
Provides tools for interacting with OpenAI API, enabling chat completions, image generation, editing, and text embeddings through various GPT and DALL-E models.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@OpenAIMCP Write a short poem about autumn leaves"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
A Model Context Protocol (MCP) server for OpenAI API access using AceDataCloud.
Interact with OpenAI models for chat completions, image generation, text embeddings, and more — directly from Claude, VS Code, or any MCP-compatible client.
Chat Completions — Access GPT-4, GPT-4o, GPT-5, o1, o3, o4-mini, and many more models
Responses API — Extended model variant support including dated releases and search-preview models
Image Generation — Create images with gpt-image-1, gpt-image-2, dall-e-3, and nano-banana models
Image Editing — Modify existing images with AI
Text Embeddings — Generate vector representations with text-embedding-3 models
Audio — Convert text to speech and transcribe audio with whisper-1 or gpt-transcribe
Related MCP server: Outsource MCP
Get an API token from AceDataCloud.
pip install mcp-openaiSet your API token:
export ACEDATACLOUD_API_TOKEN=your_api_token_heremcp-openaiTool | Description |
| Create chat completions using OpenAI models |
| Create responses using the Responses API |
| Generate images from text descriptions |
| Edit existing images with AI |
| Create text embedding vectors |
| Convert text to spoken audio |
| Transcribe audio from a URL |
| List available chat/completion models |
| List available image models |
| List available embedding models |
| Get comprehensive usage guide |
GPT-5 Series: gpt-5.5, gpt-5.5-pro, gpt-5.4, gpt-5.4-pro, gpt-5.2, gpt-5.1, gpt-5, gpt-5-mini, gpt-5-nano
GPT-4 Series: gpt-4.1, gpt-4.1-mini, gpt-4.1-nano, gpt-4o, gpt-4o-mini, gpt-4
Reasoning: o4-mini, o3, o3-mini, o3-pro, o1, o1-mini, o1-pro
gpt-image-1, gpt-image-1.5, gpt-image-2, dall-e-3, dall-e-2, nano-banana, nano-banana-2, nano-banana-pro
text-embedding-3-small, text-embedding-3-large, text-embedding-ada-002
whisper-1, gpt-transcribe
openai_chat_completion(
messages=[{"role": "user", "content": "Explain quantum computing in simple terms"}],
model="gpt-4.1"
)openai_generate_image(
prompt="A serene Japanese garden with cherry blossoms at sunset, photorealistic",
model="gpt-image-1",
size="1024x1024"
)openai_create_embedding(
input="The quick brown fox jumps over the lazy dog",
model="text-embedding-3-small"
)Variable | Description | Default |
| API token (required) | — |
| API base URL |
|
| Request timeout in seconds |
|
| MCP server name |
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| Logging level |
|
# Install dependencies
pip install -e ".[dev,test]"
# Run tests
pytest
# Run linter
ruff check .MIT
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
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