openai

openai-agents-python

Python2025–2025

openai / openai-agents-python

openai-agents-python

A lightweight, powerful framework for multi-agent workflows

AI & Machine Learning Automation & Workflows

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10Distinct people

14Mentions

0Explicit recommenders

30.6KGitHub stars

REPOSITORY AT A GLANCE

What to know before exploring

What it is

A lightweight, powerful framework for multi-agent workflows

GitHub

Where it is used

No documented product use was verified in the last source check.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

langchain-ai/langchain · linked in 2 of the same discussions
pydantic/pydantic-ai · linked in 2 of the same discussions

Mentioned in the same Hacker News threads. That is not proof they are substitutes.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 6:01:08 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by month14 dated mentions

Observed mentions: 2025-03-11 17:19:46 UTC to 2025-11-06 22:13:19 UTC.

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges

UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
Period	Start (UTC)	End (exclusive, UTC)	Mentions	Submissions	Comments
Mar 2025	2025-03-01 00:00:00 UTC	2025-04-01 00:00:00 UTC	10	2	8
Apr 2025	2025-04-01 00:00:00 UTC	2025-05-01 00:00:00 UTC	0	0	0
May 2025	2025-05-01 00:00:00 UTC	2025-06-01 00:00:00 UTC	0	0	0
Jun 2025	2025-06-01 00:00:00 UTC	2025-07-01 00:00:00 UTC	0	0	0
Jul 2025	2025-07-01 00:00:00 UTC	2025-08-01 00:00:00 UTC	2	0	2
Aug 2025	2025-08-01 00:00:00 UTC	2025-09-01 00:00:00 UTC	0	0	0
Sep 2025	2025-09-01 00:00:00 UTC	2025-10-01 00:00:00 UTC	0	0	0
Oct 2025	2025-10-01 00:00:00 UTC	2025-11-01 00:00:00 UTC	1	1	0
Nov 2025	2025-11-01 00:00:00 UTC	2025-12-01 00:00:00 UTC	1	0	1

What Hacker News says

10 sources

campbel·Mar 20, 2025

They define it in the same file https://github.com/openai/openai-agents-python/blob/48ff99bb... > An agent is an AI model configured with instructions, tools, guardrails, handoffs and more. Agents can hand off to other agents, but even the hand-off is decided by the agent itself, not a pre-defined orchestration.

In LLM Agents Are Simply Graph – Tutorial for Dummies

zh2408·Mar 20, 2025

No. It's not many agents in the workflow. It's not an agent per node. The whole workflow and the Runner class is for one agent. Check out this line: https://github.com/openai/openai-agents-python/blob/48ff99bb... A single `run_agent` is implemented based on the Runner class and workflow. So usually the workflow is for one agent (unless there is handoff).

In LLM Agents Are Simply Graph – Tutorial for Dummies

zh2408·Mar 20, 2025

By low-level, it is with respect to the agent interface. The original purpose is to help people understand how the inner agent framework is internally implemented, like those: OpenAI Agents: https://github.com/openai/openai-agents-python/blob/48ff99bb... Pydantic Agents: https://github.com/pydantic/pydantic-ai/blob/4c0f384a0626299... Langchain: https://github.com/langchain-ai/langchain/blob/4d1d726e61ed5... LangGraph: https://github.com/langchain-ai/langgraph/blob/24f7d7c4399e2...

In LLM Agents Are Simply Graph – Tutorial for Dummies

zh2408·Mar 19, 2025

I think you’re referring to function calling: https://platform.openai.com/docs/guides/function-calling This still returns a string. You need to explicitly program the branch to the right function. For example, check out how OpenAI Agents, released a week ago, rely on a workflow: https://github.com/openai/openai-agents-python/blob/48ff99bb...

In LLM Agents Are Simply Graph – Tutorial for Dummies

zh2408·Mar 19, 2025

The current implementations of Agents, e.g., OpenAI agents released last week, are based on graph (workflow): https://github.com/openai/openai-agents-python/blob/48ff99bb... Not sure about Cursor you mentioned as its agent is not open sourced.

In LLM Agents Are Simply Graph – Tutorial for Dummies

zh2408·Mar 19, 2025

Hey folks! I just posted a quick tutorial explaining how LLM agents (like OpenAI Agents, Pydantic AI, Manus AI, AutoGPT or PerplexityAI) are basically small graphs with loops and branches. For example: OpenAI Agents: for the workflow logic: https://github.com/openai/openai-agents-python/blob/48ff99bb... Pydantic Agents: organizes steps in a graph: https://github.com/pydantic/pydantic-ai/blob/4c0f384a0626299... Langchain: demonstrates the loop structure: https://github.com/langchain-ai/langchain/blob/4d1d726e61ed5... If all the hype has been confusing, this guide shows how they actually work under the hood, with simple examples. Check it out! https://zacharyhuang.substack.com/p/llm-agent-internal-as-a-...

In LLM Agents Are Simply Graph – Tutorial for Dummies

saqadri·Mar 12, 2025Submission

Show HN: MCP-Compatible OpenAI Agents SDK

Hey HN, OpenAI released the Agents SDK yesterday, which is great because of its simplicity. I just added MCP support for it, which is currently available as a fork here: https://github.com/lastmile-ai/openai-agents-mcp (and on pypi as the openai-agents-mcp package). You can specify the names of MCP servers to give an Agent access to by setting its `mcp_servers` property. The Agent will then automatically aggregate tools from the MCP servers, as well as any `tools` specified, and create a single extended list of tools. This means you can seamlessly use MCP servers, local tools, OpenAI-hosted tools, and other kinds of Agent SDK tools through a single unified syntax -- and have them interact in the same Agent run loop! Everything else stays exactly the same. ``` agent = Agent( name="MCP Assistant", instructions="You are a helpful as

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sistant with access to MCP tools.", tools=[your_other_tools], # Regular tool use for Agent SDK mcp_servers=["fetch", "filesystem"] # Names of MCP servers from your config file (see below) ) ``` The servers are configured in an `mcp_agent.config.yaml` file, very similar to how they are configured for Claude Desktop: ``` $schema: "https://raw.githubusercontent.com/lastmile-ai/mcp-agent/main..." mcp: servers: fetch: command: "uvx" args: ["mcp-server-fetch"] filesystem: command: "npx" args: ["-y", "@modelcontextprotocol/server-filesystem", "."] slack: command: "npx" args: ["-y", "@modelcontextprotocol/server-slack"] ``` I have submitted an issue and PR into the openai-agents-python repo [2], and my plan is instead of a fork, I will create an extension package for MCP support (coming later today). I was able to do this pretty quickly (got it working yesterday) because I've been building the mcp-agent library (https://github.com/lastmile-ai/mcp-agent), which makes MCP server aggregation/connection really easy. I did a Show HN about it a few weeks ago [3]. Wanted to share here to get community feedback on whether this is useful, which will help me decide if I should dedicate more time to it. [1] - https://github.com/lastmile-ai/mcp-agent [2] - https://github.com/openai/openai-agents-python/issues/23 [3] - https://news.ycombinator.com/item?id=42867050

5 points · Open discussion

koconder·Mar 12, 2025

100% but this is not the same thing, nor is this going to replace the agent SDK (or visa versa). Agents will always need some form of communication protocol, if we look at the world and agentic frameworks its a sea of logos and without some forms of open standards this would be hard. I'm currently at Comet and I have personally worked on MCP implementations AND have made some contributions to Agent SDK in the form of a native integration and improvement to test suite. - https://github.com/comet-ml/opik-mcp - https://github.com/openai/openai-agents-python/pull/91 Our recent integration shipped on day 1: - https://www.comet.com/docs/opik/tracing/integrations/openai_... I think the key to what OpenAI is pushing towards is simplicity for developers through very easy to use components. I won't comment on the strategy or pricing etc, but on fir

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st glance as a developer the simple modular approach and lack of bloat in their SDK is refreshing. Kudos to the team and people working on the edge to innovate and think differently in an already crowded and shifting landscape.

In New tools for building agents

thenameless7741·Mar 11, 2025

it's mentioned in the main thread: https://nitter.net/athyuttamre/status/1899511569274347908 > [Q] Does the Agents SDK support MCP connections? So can we easily give certain agents tools via MCP client server connections? > [A] You're able to define any tools you want, so you could implement MCP tools via function calling in short, we need to do some plumbing work. relevant issue in the repo: https://github.com/openai/openai-agents-python/issues/23

In New tools for building agents

dphuang2·Mar 11, 2025Submission

OpenAI Agents SDK

6 points · Open discussion