A
licenseA
qualityC
maintenanceEnables interaction with OpenAI-compatible model proxy APIs through MCP, supporting text generation, vision understanding, and image generation with automatic model discovery and routing.
3
MIT
OpenAI Universal Model MCP
by stevenke1981
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TDQS
B3/5.0
Scored across 18 tools
Disambiguation4/5
Most tools map to clearly distinct resources/actions (image generate vs edit, transcribe vs speech, moderation vs embeddings). There is mild overlap between openai_inspect_model, openai_get_model, openai_list_models, and openai_recommend_model, and between openai_create_response, openai_create_chat_completion, and openai_safe_api_request, but descriptions do enough to separate them. The three realtime secret/session tools are close cousins but still distinguishable by intent.
Naming Consistency4/5
All names share the openai_ prefix and overwhelmingly follow verb_noun (create_response, generate_image, transcribe_audio, list_models). A few deviate in form—openai_health_check and openai_safe_api_request read as noun/adjective phrases rather than verb_noun—but the pattern remains predictable overall.
Tool Count4/5
18 tools is on the heavier side, but the server spans models, files, responses, chat, images, audio, embeddings, moderation, and realtime, so each tool covers a genuinely different API surface. Only the model-introspection group (inspect/get/list/recommend) feels slightly padded.
Completeness3/5
Core inference surfaces are well covered, but file handling is a dead end: openai_upload_file has no list, retrieve, or delete counterpart. Broader OpenAI lifecycle areas such as batches, fine-tuning, and vector stores/assistants are absent, so agents hitting those needs will fall back to safe_api_request or fail.
Maintenance
ActivityMaintained
ResponsivenessNo recent community issues