openai-mcp-server
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- FlicenseBqualityDmaintenanceEnables interaction with OpenAI's Chat Completion and Assistants APIs, supporting assistant management, file operations, and direct queries to GPT models through standardized MCP tools.92-
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- AlicenseBqualityDmaintenanceEnables MCP-compatible clients to leverage OpenAI's multimodal capabilities (vision, image generation, speech-to-text, text-to-speech) through file-oriented tools with a security-first architecture.101MIT
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TDQS
Scored across 9 tools
Each tool maps to a distinct OpenAI capability (text, chat history, images, audio, embeddings, moderation, model discovery). openai_generate_text and openai_chat_completion are the only potentially confusable pair, but their descriptions clearly separate single-prompt/chaining from explicit message histories.
All tools share an openai_ prefix and snake_case, with mostly verb_noun names like generate_text, edit_image, list_models. openai_chat_completion and openai_text_to_speech break the verb_noun pattern slightly because they mirror API endpoint names, but the convention remains predictable.
9 tools is appropriate for an OpenAI API surface: one tool per major modality (text, image, audio, embeddings, moderation) plus model discovery. No tool feels redundant or missing at the count level.
The set covers text generation, chat completions, image generation/editing, transcription, speech synthesis, embeddings, and moderation, which are the core OpenAI workflows. Minor gaps exist—notably no vision/analysis of image inputs and no fine-tuning/batch management—but agents can accomplish typical tasks without dead ends.