MCP server for OpenAI API (chat completions, image generation, embeddings) via AceDataCloud
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.
The AceDataCloud distribution is mcp-openai-pro. The unrelated
mcp-openai package on PyPI is not maintained by AceDataCloud. Update existing
uvx configurations to the new package name; the hosted MCP URL is unchanged.
Get an API token from AceDataCloud.
pip install mcp-openai-pro
Set your API token:
export ACEDATACLOUD_API_TOKEN=your_api_token_here
mcp-openai-pro
| Tool | Description |
|---|---|
openai_chat_completion | Create chat completions using OpenAI models |
openai_create_response | Create responses using the Responses API |
openai_generate_image | Generate images from text descriptions |
openai_edit_image | Edit existing images with AI |
openai_create_embedding | Create text embedding vectors |
openai_text_to_speech | Convert text to spoken audio |
openai_transcribe_audio | Transcribe audio from a URL |
openai_list_chat_models | List available chat/completion models |
openai_list_image_models | List available image models |
openai_list_embedding_models | List available embedding models |
openai_get_usage_guide | Get comprehensive usage guide |
:official variants settle from actual text-input, image-input, and image-output tokens.text-embedding-ada-002 is retired. Re-embed documents and rebuild existing indexes
when migrating; do not mix old-model vectors with text-embedding-3 vectors.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 |
|---|---|---|
ACEDATACLOUD_API_TOKEN | API token (required) | — |
ACEDATACLOUD_API_BASE_URL | API base URL | https://api.acedata.cloud |
OPENAI_REQUEST_TIMEOUT | Request timeout in seconds | 60 |
MCP_SERVER_NAME | MCP server name | openai |
LOG_LEVEL | Logging level | INFO |
# Install dependencies
pip install -e ".[dev,test]"
# Run tests
pytest
# Run linter
ruff check .
MIT
Source-derived launch command. Check the maintainer’s required arguments and credentials before running:
uvx mcp-openai-proMerge this template into ~/Library/Application Support/Claude/claude_desktop_config.json. Keep existing servers. Add any arguments, credentials, and permissions required by the maintainer; this template has not been install-tested.
{
"mcpServers": {
"io-github-acedatacloud-mcp-openai": {
"command": "uvx",
"args": [
"mcp-openai-pro"
]
}
}
}Restart Claude Desktop completely for changes to take effect. Confirm the server appears connected in the client’s tool list, then try a read-only example from its documentation.
Claude Desktop setup referencemcp-openai-propypiio.github.AceDataCloud/mcp-openai works with any MCP-compatible client. Copy the config snippet from the Configuration section above and add it to the file shown for your client, then restart the application.
~/Library/Application Support/Claude/claude_desktop_config.jsonRestart Claude Desktop completely for changes to take effect.~/.cursor/mcp.jsonRestart Cursor for changes to take effect..vscode/mcp.jsonReload VS Code window for changes to take effect.~/.codeium/windsurf/mcp_config.jsonRestart Windsurf for changes to take effect..mcp.jsonSave at the project root, then start Claude Code in that project and review the MCP server approval prompt. Keep real credentials out of shared files.