"Building OpenAI Agents SDK Using Official Documentation" matching MCP servers:

Query OpenAI models directly from Claude using MCP protocol.

Lets an AI coding agent offload low-complexity, monotonous tasks to a cheap local or OpenAI-compatible model that runs its own server-side tool loop for reading, searching, and staging file writes, so large file contents and intermediate steps never enter the caller's context. Also provides summaries, extraction, classification, bulk file mapping, staged-diff review, model management, and session token-savings reporting.

Enables running AI agents via OpenAI-compatible APIs with custom system prompts, models, and queries. Supports persistent memory, preset agents, and multi-step workflows like pipelines and swarms.

Autonomous, carbon-aware building management system that pairs EnergyPlus digital twins with LLMs via the Model Context Protocol (MCP) for dynamic HVAC optimization and grid carbon reduction.

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 an orchestrator like Claude Code to hand coding work off to Cursor SDK agents, run as detached background jobs that survive the session and can be listed, inspected, steered, resumed, or stopped. Agents are asynchronous and reusable across follow-up turns, letting expensive frontier models delegate cheaply without blocking or paying to read the results.

Enables AI assistants to delegate specific tasks to specialized sub-agents (e.g., test-writer, code-reviewer). Supports both Cursor and Claude Code with custom agent definitions.

Enables an AI agent to launch, monitor, and steer multiple coding agents running in tmux panes, including sending keystrokes, waiting for idle or output patterns, and managing sessions.

Enables local deterministic discovery, validation, and selection of validated skills through MCP tools, producing consistent plans without executing any skill.

Enables orchestrating multiple specialist Claude Code agents as a team, with live visualization and agent-to-agent messaging.

nexus-agents makes your AI coding tools work together intelligently. It coordinates Claude, Codex, Gemini, and OpenCode — routing each task to the best model using data-driven algorithms, validating outputs through multi-model consensus voting, and continuously improving through outcome-driven learning. Connect it to any MCP-compatible editor (Claude Code, Cursor, VS Code) and it handles the rest.

The simplest way to bridge and collaborate across AI Agent sessions like Claude Code, Codex, Gemini, or Cursor. It allows your agents to combine their strengths to solve your most difficult tasks without leaving their current context.

Enables running isolated main and sub agent tasks in networkless Docker capsules with explicit input grants, verified artifact delivery, and independent reviewer oversight via MCP tools.

MCP server that enables AI agents to autonomously buy virtual phone numbers and receive SMS verification codes. Supports multiple providers (5sim, SMS-Activate, OnlineSim) with automatic cheapest-provider selection.

Enhances Claude Code's Task tool with session resumption and independent agent execution, allowing autonomous subagents from .claude/agents/ with true parallel batch support.

Enables multiple AI agents using MCP-compatible clients to collaborate in parallel on the same project across one or more machines, with direct messaging, a shared task board, atomic file/folder locking, presence tracking, and a live web dashboard.

Enables listing, inspecting, chatting with, and waking deployed Voight Agents from any MCP client, including checking agent state, usage, tasks, and GPU status.

Enables coding agents to publish and read events on channels, notify humans, and ask yes/no, multiple-choice, or free-text questions, returning answers as tool results.

A simple server that acts as a Master Control Program (MCP) for unified interaction with OpenAI and Anthropic (Claude) AI models through a single API endpoint.

A lightweight framework for building and orchestrating AI agents through the Model Context Protocol, enabling users to create scalable multi-agent systems using only configuration files.