"OpenAI Gym" matching MCP servers:

Exposes the OpenAI Admin API as MCP tools, enabling management of organization members, projects, service accounts, API keys, rate limits, usage, costs, and audit logs through natural language.

Typed MCP server for OpenAI Ads and ChatGPT Ads via the Advertiser API. Supports account, campaign, ad group, ad, creative, audience, insight, and conversion tools with readonly mode and guarded writes.

A Model Context Protocol server that enables Claude users to access specialized OpenAI agents (web search, file search, computer actions) and a multi-agent orchestrator through the MCP protocol.

Provides tools for file system operations and text generation using OpenAI-compatible models via the Model Context Protocol, supporting both stdio and HTTP transports.

A lightweight bridge that wraps OpenAI's built-in tools (like web search and code interpreter) as Model Context Protocol servers, enabling their use with Claude and other MCP-compatible models.

Query OpenAI models directly from Claude using MCP protocol.

Connects AI assistants to a user's Codeforces account and live platform data, enabling problem discovery, submission review, rating tracking, contest planning, and friends or gym access through natural-language queries.

An MCP server that provides expert knowledge on the OpenAI API, powered by RAG. It enables users to ask technical questions and get accurate answers, with support for search and fetch tools.

Exposes Gemini CLI's built-in tools and external MCP proxies through a unified MCP endpoint while providing an OpenAI-compatible API for Gemini models. It features configurable security modes to safely manage file system operations, web searches, and shell command execution.

Enables image analysis via OpenAI-compatible vision APIs, supporting local files, URLs, and base64 inputs with intelligent tiling for high-resolution images. Provides a secure, configurable MCP stdio server for structured vision analysis.

A minimal server/client application implementation utilizing the Model Context Protocol (MCP) and Azure OpenAI.

MCP server that wraps OpenAI's gpt-image-2 image generation API, enabling image generation from text prompts, listing saved images, and loading images inline.

An MCP server that provides deep knowledge about OpenAI APIs and SDKs, enabling users to query technical information through various MCP clients including ChatGPT Deep Research, Cursor, and OpenAI Responses API.

Provides intelligent OpenAI API token management with automatic switching between model tiers when usage limits are reached. It enables users to track daily token consumption, estimate costs before making calls, and manage project-specific usage data.

An MCP server that enables image generation and editing using OpenAI's DALL-E models with support for text prompts, inpainting, and outpainting. It includes advanced features like automatic aspect ratio mapping and intelligent file management to handle large image payloads.

Enables image generation using OpenAI's DALL-E and GPT-Image models directly through the Model Context Protocol. It allows users to create and save images with fine-grained control over parameters like size, quality, and background transparency.

Enables logging workouts, sets, routines, food, water, and macros through natural-language chat in any MCP client, with OAuth-based secure access and timezone-aware daily tracking.

An MCP server that exposes the ChatGPT Ads API as tools an LLM host can call.

An MCP tool server that enables generating and editing images through OpenAI's image models, supporting text-to-image generation and advanced image editing (inpainting, outpainting) across various MCP-compatible clients.

Provides AI agents and coding assistants with image generation and editing capabilities using OpenAI's GPT-image-1 model, with support for local or Supabase storage.

This server enables semantic search capabilities using Qdrant vector database and OpenAI embeddings, allowing users to query collections, list available collections, and view collection information.

Provides LLMs with live access to Binghamton University campus data, including laundry availability, bus locations, dining status and menus, gym capacity, library room availability, and campus events.

A Model Context Protocol server implementation that enables connection between OpenAI APIs and MCP clients for coding assistance with features like CLI interaction, web API integration, and tool-based architecture.

Enables agents to track workouts, body metrics, and training stats for registered users through a JSON-RPC MCP endpoint, with scoped agent permissions and a web dashboard.

Provides comprehensive management of OpenAI Vector Stores, allowing AI assistants to upload files, manage vector databases, and handle batch operations via the OpenAI API. It supports multiple deployment methods, including Cloudflare Workers and local NPM installation, for seamless integration with MCP-compatible clients.

A lightweight remote MCP server for generating images using OpenAI's image models, exposing a generate_image tool.

Enables text-only language models to understand images by forwarding image and prompt requests to vision model backends via MCP, returning descriptive text. Supports multiple OpenAI-compatible providers with task routing and safety checks.

Zero-dependency MCP server that equips text-only LLMs (e.g., DeepSeek) with vision by converting images to text descriptions via OpenAI-compatible vision APIs, exposing an img2text tool with multi-provider fallback.

Enables MCP-capable chats and agents to generate images, video, and audio through OpenAI, Google Gemini, fal.ai, and Cloudflare Workers AI, optionally routed via Cloudflare AI Gateway. Supports image editing, asynchronous video jobs, and text-to-speech with per-request provider and model overrides, and can run over stdio or streamable HTTP.

A self-hostable, open-source, semantically-searchable Agent Skills registry delivered over MCP, with a three-tier progressive disclosure architecture.