openai-agents-sdk

Build AI agents with the OpenAI Agents SDK and MCP server integration.

2|Updated Dec 4, 2025
One-click install
npx skills add https://github.com/NaimalArain13/Hackathon-II_The-Evolution-of-Todo --skill openai-agents-sdk-naimalarain13
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: openai-agents-sdk
Source: https://github.com/NaimalArain13/Hackathon-II_The-Evolution-of-Todo/tree/main/.claude/skills/openai-agents-sdk
Command: npx skills add https://github.com/NaimalArain13/Hackathon-II_The-Evolution-of-Todo --skill openai-agents-sdk-naimalarain13

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill enables building AI agents using the OpenAI Agents SDK with MCP server integration.

Core Features & Use Cases

  • Agent creation and configuration with Gemini via AsyncOpenAI or OpenRouter for alternative models
  • Function tools, handoffs, and MCP server connections to manage conversations
  • Real-world workflows: rapid development of autonomous agents with cloud-native MCP integration

Quick Start

Install the SDK and set up credentials:

  • pip install openai-agents
  • Ensure GOOGLE_API_KEY is set for Gemini direct integration or OPENROUTER_API_KEY for OpenRouter
  • Create a minimal agent and connect to an MCP server to run a simple query

Frequently Asked Questions about openai-agents-sdk

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build AI agents with Python using the OpenAI Agents SDK?

To build AI agents with Python, you install the OpenAI Agents SDK via pip and configure environment variables for API keys. You can then create agents, define function tools, and manage conversations through the SDK's core interfaces.

Can I use Gemini or OpenRouter models instead of OpenAI for my AI agents?

Yes, you can use Gemini or OpenRouter models for your AI agents. The SDK supports Gemini via AsyncOpenAI or OpenRouter integration by setting the GOOGLE_API_KEY or OPENROUTER_API_KEY environment variables instead of requiring an OpenAI API key.

How does MCP server integration work with AI agents?

MCP server integration works by connecting your AI agents to an external MCP server endpoint. This allows the agents to leverage the server's capabilities for managing conversations and executing function tools across different services.

What do I need to set up before creating an AI agent with function tools and handoffs?

Before creating an AI agent with function tools and handoffs, you need Python tooling with the openai-agents package installed. You also need to configure the required API keys and have access to an MCP server endpoint for connection.

What is the best way to manage multi-agent handoffs in Python?

The best way to manage multi-agent handoffs in Python is using the OpenAI Agents SDK, which provides built-in support for routing tasks between agents. You can configure handoffs alongside function tools and MCP server connections to handle complex workflows.

Are there limitations when using OpenRouter with the OpenAI Agents SDK?

When using OpenRouter with the OpenAI Agents SDK, you must ensure the OPENROUTER_API_KEY is properly set and that your MCP server endpoint is accessible. Non-OpenAI models may have specific configuration requirements via AsyncOpenAI to function correctly.