OpenAI API MCP Server
APIs for sampling from and fine-tuning language models
Quick Setup
Transport: STDIO
Command: npx -y @mcp/openai-com
Environment Variables
OPENAI_API_API_KEYExample: your_openai_api_api_key
MCP Server Configuration
Add this to your claude_desktop_config.json or Cursor MCP settings.
{
"mcpServers": {
"openai-com": {
"command": "npx",
"args": ["-y","@mcp/openai-com"],
"env": {
"OPENAI_API_API_KEY": "your_openai_api_api_key"
}
}
}
}Endpoints
/answersAnswers the specified question using the provided documents and examples. The endpoint first [searches](/docs/api-reference/searches) over provided documents or files to find relevant context. The relevant context is combined with the provided examples and question to create the prompt for [completion](/docs/api-reference/completions).
/audio/transcriptionsTranscribes audio into the input language.
/audio/translationsTranslates audio into into English.
/chat/completionsCreates a completion for the chat message
/classificationsClassifies the specified `query` using provided examples. The endpoint first [searches](/docs/api-reference/searches) over the labeled examples to select the ones most relevant for the particular query. Then, the relevant examples are combined with the query to construct a prompt to produce the final label via the [completions](/docs/api-reference/completions) endpoint. Labeled examples can be provided via an uploaded `file`, or explicitly listed in the request using the `examples` parameter for quick tests and small scale use cases.
/completionsCreates a completion for the provided prompt and parameters
/editsCreates a new edit for the provided input, instruction, and parameters.
/embeddingsCreates an embedding vector representing the input text.
/enginesLists the currently available (non-finetuned) models, and provides basic information about each one such as the owner and availability.
/engines/{engine_id}Retrieves a model instance, providing basic information about it such as the owner and availability.