OpenAI Deep Research

Workflow

Features

• PDF export

MCP Server

from openai import OpenAI

client = OpenAI()

instructions = "<deep research instructions...>"

resp = client.responses.create(
    model="o3-deep-research",
    background=True,
    reasoning={
        "summary": "auto",
    },
    tools=[
        {
            "type": "mcp",
            "server_label": "mycompany_mcp_server",
            "server_url": "https://mycompany.com/mcp",
            "require_approval": "never",
        },
    ],
    instructions=instructions,
    input="What similarities are in the notes for our closed/lost Salesforce opportunities?",
)

print(resp.output_text)

Review

We Tried OpenAI’s New Deep Research—Here’s What We Found

Vibe check: It’s awesome.

https://every.to/chain-of-thought/we-tried-openai-s-new-deep-research-here-s-what-we-found

Introducing deep research

An agent that uses reasoning to synthesize large amounts of online information and complete multi-step research tasks for you. Available to Pro users today, Plus and Team next.

https://openai.com/index/introducing-deep-research/

Deep research System Card

This report outlines the safety work carried out prior to releasing deep research including external red teaming, frontier risk evaluations according to our Preparedness Framework, and an overview of the mitigations we built in to address key risk areas.

https://openai.com/index/deep-research-system-card/

Deep Research API

Deep Research API with the Agents SDK | OpenAI Cookbook

This cookbook demonstrates how to build Agentic research workflows using the OpenAI Deep Research API and the OpenAI Agents SDK. It is a...

https://cookbook.openai.com/examples/deep_research_api/introduction_to_deep_research_api_agents