OpenAI Agents SDK
OpenAI's minimal Python framework for agent handoffs, not graphs.
Overview
The OpenAI Agents SDK is a free, open-source Python and JS framework for multi-agent workflows built around a handful of primitives — agents, handoffs, tools, guardrails and tracing. It works with OpenAI's APIs plus 100+ other models via LiteLLM, despite the branding.
Pricing
Pricing shown for reference only. These figures reflect RECATOOLS research as of 12 Jul 2026 and may be out of date or incomplete. This is not financial or purchasing advice — always confirm the current price on the provider’s official website before making any decision.
What you can produce with OpenAI Agents SDK
- Core primitives: agents, handoffs, tools, guardrails, sessions
- Built-in tracing for debugging agent runs
- Provider-agnostic via LiteLLM (100+ models beyond OpenAI)
- Python and JavaScript/TypeScript SDKs
- Open source and free to use
- Works with OpenAI Responses and Chat Completions APIs
ASEAN Perspective
OpenAI Agents SDK in Southeast Asia
ASEAN-region availability and pricing notes coming soon. Drop the editorial team a note via /contact/ if you can supply local context (Singapore/Malaysia/Indonesia/Thailand/Vietnam).
OpenAI's Agents SDK is the deliberately small option in a field of increasingly elaborate agent frameworks: a handoff pattern with guardrails and tracing gets you a working multi-agent setup in well under 100 lines, which appeals to teams who found LangGraph's graph-and-state model heavier than they needed. It's provider-agnostic in practice — LiteLLM support means 100+ non-OpenAI models work despite the name — though the ecosystem and community size lag well behind LangGraph, which pulls tens of millions of monthly downloads and has production references at real scale (Klarna, for one). Comparisons consistently put LangGraph ahead on cost efficiency and fine-grained control for complex orchestration, and the Agents SDK ahead on speed to a working prototype. Pick it for fast GPT-native multi-agent builds, not for a system that needs explicit graph control.
What people say
Head-to-head comparisons written throughout 2026 consistently place the OpenAI Agents SDK as the lightweight option against LangGraph's more structured, graph-based approach — and the two frameworks solve orchestration differently enough that the write-ups read less like a ranking and more like a fit exercise. LangGraph models workflows as a directed graph with typed state and explicit edges; the Agents SDK gives you four primitives (agents, handoffs, guardrails, tracing) and lets you wire them together with regular code.
The numbers people cite: LangGraph pulls around 39.2 million monthly PyPI downloads and has been cited running at Klarna's scale (reportedly 85 million users), while the Agents SDK's own GitHub repo (openai/openai-agents-python) sits at roughly 3,300 stars — a fraction of LangGraph's footprint, though a younger project by comparison. Reviewers who prefer the Agents SDK point to getting a working handoff-based multi-agent system running in under 100 lines of code, versus more boilerplate to reach the same result in LangGraph.
On cost and lock-in: despite the OpenAI branding, the SDK is provider-agnostic via LiteLLM, supporting 100+ models beyond OpenAI's own Responses and Chat Completions APIs — reviewers note this defuses the obvious lock-in concern, though LangGraph is still generally rated ahead on cost efficiency at scale because its explicit graph edges avoid the token overhead of LLM-driven routing decisions that frameworks like CrewAI incur.
The consistent bottom line across comparison pieces: pick the Agents SDK for a fast, GPT-native path to a working multi-agent prototype with built-in tracing for debugging; pick LangGraph when you need fine-grained control over complex, stateful orchestration and are willing to accept more setup work for it. Neither framework carries a licensing cost — both are open source, so the real cost is entirely in the underlying model API calls. Worth noting for teams evaluating both: the Agents SDK also ships voice-agent primitives built on OpenAI's Realtime API, a use case LangGraph doesn't natively cover, which occasionally tips the decision for anyone building voice interfaces rather than pure text agents.
Summary of public user & expert reviews, compiled by RECATOOLS.
About this listing
This entry was compiled from publicly available data including OpenAI Agents SDK's official website, press releases, documentation, and reputable third-party publications. RECATOOLS is not affiliated with OpenAI Agents SDK unless explicitly stated.
Third-party AI tools update their pricing, features, availability, and policies frequently. Information here may be outdated by the time you read this — we make reasonable efforts to keep listings current, but cannot guarantee absolute accuracy.
For the latest details, please refer to OpenAI Agents SDK directly →
Spotted something out of date? Suggest an update →
OpenAI Agents SDK in the news
Alternatives to OpenAI Agents SDK
More in Agents & Automation
