"OpenAI Gym" matching MCP servers:

Enables Claude to perform real-time web searches and fetch web page content via MCP, using OpenAI-compatible APIs with optional Tavily or Firecrawl engines.

Provides intelligent web search capabilities using OpenAI's reasoning models, enabling AI assistants to fetch up-to-date information with smart reasoning.

Enables semantic search, code exemplar lookup, knowledge-graph statistics, and cached retrieval over locally ingested notebook and Markdown content through MCP.

MCP server providing 24 tools to access public, real-time Purdue University data including dining menus, gym occupancy, course catalogs, bus times, events, and more.

One click installation & Configuration，access to OpenAI's websearch functionality through the Model Context Protocol。

Enables Claude to directly invoke OpenAI's chat models (GPT-4o, GPT-4o-mini, o1-preview, o1-mini) through a Model Context Protocol integration, allowing users to query and compare responses from different AI models within Claude Desktop.

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.

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.

Provides semantic search and document retrieval via OpenAI Vector Store API, extending ChatGPT Deep Research with custom knowledge and tools.

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.

Provides MCP tools to list and search OpenAI Agents SDK documentation, enabling LLMs to retrieve documentation topics and content via natural language queries.

Provides access to OpenAI's advanced models (including o3) with integrated web search, Python code interpreter, and combined analysis capabilities. Enables users to perform web searches, execute code in sandboxed environments, and combine search with analysis through natural language.

Lightweight MCP server using OpenAI Responses API with built-in web search, enabling AI assistants to answer questions with citations and search results.

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.

Provides intelligent web search capabilities using OpenAI's Web Search API with reasoning models. Supports localized results, multiple model options, and automatic source citations for current information retrieval.

Enables semantic search and document retrieval from OpenAI Vector Store, allowing users to search documents using natural language queries and fetch complete document contents through ChatGPT.

Exposes hybrid retrieval (dense embeddings + BM25 + RRF) and document operations (search, fetch, rerank) as MCP tools, using Qdrant and OpenAI embeddings for local or server mode.

Search and harvest Korean academic literature and book bibliography metadata from the National Library of Korea Seoji OpenAPI via MCP or CLI.

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