OpenAI Agents SDK
Framework for building agents with tools, handoffs, guardrails, tracing, and model orchestration.
Best for
Deployment targets
Source boundary
OpenAI documentation describes agents, tools, handoffs, guardrails, and tracing as core SDK concepts.
| Source | Type | Verified | Citation |
|---|---|---|---|
| OpenAI Agents SDK docs | docs | 2026-09-15 | Documents the SDK concepts used for agent orchestration. |
| OpenAI Agents SDK GitHub | github | 2026-09-15 | Public repository for the Python SDK implementation. |
Relationships
| Type | Source | Target | Confidence |
|---|---|---|---|
| best_for | openai-agents-sdk | coding-agent | 0.78 |
| supports | openai-agents-sdk | tool-calling | 0.92 |
Compatibility
| Type | Target | Status | Evidence |
|---|---|---|---|
| framework_mcp | github-mcp-server | verify_required | Both entries participate in agent tool orchestration, but a production integration should verify transport, auth, and runtime assumptions. |
| runtime_deployment | serverless-container-runtime | verify_required | OpenAI Agents SDK workflows can be deployed in server or container environments, but production runtime assumptions should verify process lifetime, secrets, network access, and tracing setup. |
How should teams choose between OpenAI Agents SDK and LangChain / LangGraph?
Choose based on workflow shape, integration breadth, and operational requirements. OpenAI Agents SDK is a focused fit for OpenAI-native agent orchestration, while LangChain / LangGraph is stronger when graph runtime and broad integrations are central.
When is Microsoft Agent Framework a better fit than OpenAI Agents SDK?
Microsoft Agent Framework is a better fit when Python and .NET coverage, Microsoft platform alignment, or enterprise workflow integration matter. OpenAI Agents SDK is a better fit for OpenAI-native orchestration with handoffs, guardrails, and tracing.