openai-responses

Manage stateful AI conversations and tool-driven workflows via OpenAI Responses API and MCP servers.

204|30|Updated Nov 8, 2025

Search Tags:#MCP #tooling #streams #stateful AI #responses API

Ready to run

npx skills add https://github.com/secondsky/claude-skills --skill openai-responses-secondsky

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: openai-responses
Source: https://github.com/secondsky/claude-skills/tree/main/plugins/openai-responses/skills/openai-responses
Command: npx skills add https://github.com/secondsky/claude-skills --skill openai-responses-secondsky

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

The OpenAI Responses API enables stateful AI agents with polymorphic outputs, MCP support, and long-running workflows.

Core Features & Use Cases

Stateful conversations: Preserve reasoning and context across turns.
Built-in tools: Code interpreter, web search, file search, etc.
MCP & workflows: External tool integrations via MCP servers.

Quick Start

Install SDK, create a simple stateful response, and iterate with built-in tools.

Frequently Asked Questions about openai-responses

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

FAQPage Schema

How do I build stateful AI agents with the OpenAI Responses API?▼

The Responses API manages stateful AI conversations by preserving context and reasoning across multiple turns. It enforces conversation_id persistence, enabling agents to maintain state while executing tools and reasoning through multi-step workflows without losing context between interactions.

Can I integrate MCP servers with OpenAI's built-in tools?▼

Yes. The Responses API supports external MCP server integrations alongside built-in tools like code interpreter, web search, and file search. This enables polymorphic tool execution where agents can route tasks to either native tools or external MCP-connected services based on workflow requirements.

What's the best way to handle long-running AI workflows with tool execution?▼

Use server-side tool execution with automatic state management through the Responses API. It handles conversation threading and background task persistence, allowing agents to execute tools asynchronously while maintaining session state across code interpretation, searches, and external MCP operations.

How do I manage polymorphic outputs in multi-turn agent conversations?▼

The Responses API enforces structured output handling across tool responses and reasoning steps. It manages variable output types from different tools—code results, search data, generated images—and routes them consistently through the conversation state, ensuring agents can process diverse outputs in a single session.

Do I need separate infrastructure to run stateful agentic workflows?▼

No. The Responses API abstracts server-side state management and tool orchestration, so you configure conversation_id and tool settings without managing separate backend infrastructure. It handles persistence and execution across built-in and MCP tools automatically.