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Generate completions, list models, create embeddings, and transcribe audio via OpenAI API
420+ deploysYour AI agent gets 5 capabilities in one connection. Deploy once, use from any client.
POST endpoints
create_chat_completion
Send a prompt to a GPT model. Required: 'model' (gpt-4o, gpt-4o-mini, o1), 'messages' array [{role, content}]. Optional: 'temperature' (0-2), 'max_tokens', 'tools' (function calling), 'response_format' ({type:'json_object'}), 'stream' (true for SSE). Returns choices[].message with content and optional tool_calls.
https://api.openai.com/v1/chat/completions
create_embedding
Generate vector embeddings. Required: 'model' (text-embedding-3-small or text-embedding-3-large), 'input' (string or string[]). Optional: 'dimensions' (256-3072, smaller = faster search). Returns data[].embedding (float array). Batch up to 2048 inputs per call for efficiency.
https://api.openai.com/v1/embeddings
generate_image
Generate images from text. Required: 'prompt' (max 4000 chars for dall-e-3). Optional: 'model' (dall-e-3 or dall-e-2), 'n' (1 for dall-e-3, 1-10 for dall-e-2), 'size' (1024x1024, 1792x1024, 1024x1792), 'quality' (standard or hd), 'response_format' (url or b64_json). Returns data[].url or data[].b64_json.
https://api.openai.com/v1/images/generations
transcribe_audio
Transcribe audio to text. Required: 'file' (multipart upload, max 25MB), 'model' (whisper-1). Optional: 'language' (ISO-639-1), 'response_format' (json, text, srt, verbose_json, vtt), 'timestamp_granularities' (['word','segment']). Supports mp3, mp4, mpeg, mpga, m4a, wav, webm.
https://api.openai.com/v1/audio/transcriptions
GET endpoints
list_models
List all available models. Returns data[] with id, object, created (unix timestamp), and owned_by. Filter client-side by prefix (gpt-4, dall-e, whisper, tts). No pagination needed.
https://api.openai.com/v1/models
Connect OpenAI API to Claude Code with one command:
claude mcp add openai https://datafaucet.dev/api/mcp/t/openai{notion_token}) with your real credentialsNeed API keys? Try our free sandbox templates first to see MCP in action with zero setup.
Replace these placeholders with your real values before deploying:
{audio_url}Your value{image_prompt}Your value{openai_api_key}API settings page{prompt}Your value{text}Your valuePreview:
POST https://api.openai.com/v1/chat/completions Authorization: Bearer {openai_api_key} Content-Type: application/json {"model":"gpt-4o","messages":[{"role":"user","content":"{prompt}"}],"max_tokens":1024}
claude mcp add openai --url https://datafaucet.dev/api/mcp/t/openai
Paste into your client's MCP configuration file · most users connect in under 60s
claude mcp add openai --url https://datafaucet.dev/api/mcp/t/openaiWhat your AI agent sees
I have access to 5 tools from OpenAI API: create_chat_completion, list_models, create_embedding, and 2 more.
“Send a prompt to a GPT model. Required: 'model' (gpt-4o, gpt-4o-mini, o1), 'messages' array [{role, content}]. Optional: 'temperature' (0-2), 'max_tokens', 'tools' (function calling), 'response_format' ({type:'json_object'}), 'stream' (true for SSE). Returns choices[].message with content and optional tool_calls.”
Calling create_chat_completion... Done. Here are the results.
Try these prompts
“Send a prompt to a GPT model. Required: 'model' (gpt-4o, gpt-4o-mini, o1), 'messages' array [{role, content}]. Optional: 'temperature' (0-2), 'max_tokens', 'tools' (function calling), 'response_format' ({type:'json_object'}), 'stream' (true for SSE). Returns choices[].message with content and optional tool_calls”
Copy“List all available models. Returns data[] with id, object, created (unix timestamp), and owned_by. Filter client-side by prefix (gpt-4, dall-e, whisper, tts). No pagination needed”
Copy“Generate vector embeddings. Required: 'model' (text-embedding-3-small or text-embedding-3-large), 'input' (string or string[]). Optional: 'dimensions' (256-3072, smaller = faster search). Returns data[].embedding (float array). Batch up to 2048 inputs per call for efficiency”
CopyClick any prompt to copy, then paste into your AI client.