Claude Agent SDK vs OpenAI Agents SDK 2026
Source-reviewed June 2026 comparison of Anthropic Claude Agent SDK vs OpenAI Agents SDK. Use it to compare orchestration ownership, tools, MCP, handoffs, subagents, sessions, security review, observability, cost measurement, and migration risk.
Official-doc source check
This page was rewritten to remove stale release-date, pricing, version, and API-shape claims. It now routes the decision through official provider docs and provider-neutral engineering checks.
Decision checks
- - Use OpenAI Agents SDK when your application owns orchestration, tools, state, approvals, handoffs, tracing, and runtime behavior on the OpenAI platform.
- - Use Claude Agent SDK when you want Claude Code as a programmable library for file, command, edit, MCP, session, hook, and development-automation workflows.
- - Benchmark cost from traces and current provider pricing rather than fixed per-conversation estimates.
- - Treat security as a deployment property: permissions, sandboxing, credentials, approvals, logging, and reversible actions matter more than SDK branding.
SDK feature comparison (source-reviewed June 2026)
| Feature | Claude Agent SDK | OpenAI Agents SDK |
|---|---|---|
| Best fit | Claude Code-style programmable worker | Application-owned agent runtime |
| Languages documented | Python and TypeScript | Python and TypeScript |
| Tool model | Claude Code tools, custom tools, MCP, permissions | Hosted tools, function tools, MCP, approvals |
| Multi-agent model | Subagents and tool-style delegation | Handoffs or agents-as-tools |
| State | Sessions and transcript utilities | History, sessions, app storage, or Conversations API |
| Observability | Cost/usage tracking plus SDK workflow inspection surfaces | Built-in tracing in normal server-side SDK path |
| Security decision | Configure tools, permissions, hooks, hosting, and approvals | Configure tools, guardrails, approvals, tracing, and sandboxing |
| Cost decision | Measure traces against current Anthropic pricing | Measure traces against current OpenAI pricing |
Frequently asked questions
What are the architectural differences between Claude Agent SDK and OpenAI Agents SDK?
The practical difference is where the agent control plane lives. OpenAI describes the Agents SDK as the path to use when your server owns orchestration, tool execution, state, approvals, tracing, and runtime behavior, with typed TypeScript or Python application code. Anthropic describes the Claude Agent SDK as Claude Code as a library: Python or TypeScript code can use the same agent loop, tools, and context management that power Claude Code. In short: choose OpenAI Agents SDK when you want an OpenAI-platform-centered agent runtime with handoffs, tools, guardrails, tracing, and server-managed orchestration; choose Claude Agent SDK when you specifically want Claude Code-style file, command, editing, session, and project automation behavior inside your own program.
How does multi-agent orchestration compare?
OpenAI documents two core orchestration patterns: handoffs, where a specialist agent takes over a branch of work, and agents-as-tools, where a manager agent keeps ownership and calls specialists as bounded capabilities. Claude Agent SDK exposes Claude Code-style subagents, sessions, MCP, custom tools, hooks, slash commands, skills, and plugins through the SDK surface. The safer comparison is not "which is more powerful" but "which ownership model fits the workflow": use handoffs when delegated ownership should move to a specialist, use agents-as-tools or subagents when a supervisor should keep control and collect results from specialized workers.
What about tool execution and security?
Do not treat either SDK as a security boundary by itself. OpenAI documents hosted tools, function tools, MCP, approvals, guardrails, tracing, and sandbox patterns; Anthropic documents built-in Claude Code tools, custom tools, MCP servers, permissions, user approvals, hooks, checkpointing, and hosting guidance. Security depends on tool permissions, credential scope, sandboxing, network access, file-system access, audit logs, and human review. For production, isolate dangerous work, validate tool input, sanitize tool output, scope OAuth/API credentials, log every tool call, and require approvals for irreversible actions.
How do session management and memory differ?
OpenAI documents several continuation strategies for agents: replaying result history, using SDK sessions, using your own storage, or using OpenAI Conversations API when shared server-managed state is appropriate. Claude Agent SDK exposes session-oriented APIs and utilities such as listing prior sessions and reading session messages. For long-running production agents, keep durable business state in your own database and treat SDK session history as execution context, not as the only system of record.
What does each SDK cost in production?
Do not estimate agent cost from a single model-price row. Agent cost depends on model choice, number of model turns, tool-call fanout, retries, web/file/computer tools, hosted tool charges, prompt caching, storage, sandbox runtime, tracing retention, and human-review steps. The right comparison is a measured trace: run the same workflow in both SDKs, record model calls, input/output tokens, tool calls, retries, latency, and success rate, then multiply by current provider pricing pages. This page intentionally avoids fixed per-conversation dollar claims because pricing and model availability change.
Which SDK has better observability?
OpenAI docs state that tracing is built into the Agents SDK and normally enabled by default in the server-side SDK path, including model calls, tool calls, handoffs, guardrails, and custom spans. Claude Agent SDK docs expose cost/usage tracking, sessions, hooks, tool execution, and deployment controls, and the broader Claude Code ecosystem supports inspectable agent workflows. For production, require trace IDs, tool-call payload redaction, error/retry grouping, cost aggregation, and workflow-level success metrics regardless of provider.
How portable is code between SDKs?
Migration friction is real because tool contracts, run objects, streaming events, session semantics, approvals, and tracing metadata differ. Anthropic also documents an OpenAI SDK compatibility layer for testing Claude through OpenAI-style clients, but it says the compatibility layer is mainly for evaluation and is not the best long-term production path for most Claude API use cases. For portability, keep domain tools behind your own service boundary, store durable state in your database, write provider-neutral evals, and isolate provider-specific orchestration in a thin adapter.
When should I choose Claude Agent SDK vs OpenAI Agents SDK?
Choose Claude Agent SDK when the product is essentially Claude Code as a programmable worker: repository automation, file edits, shell commands, MCP-connected development tools, sessions, hooks, and Claude-native behavior. Choose OpenAI Agents SDK when your application server owns the agent workflow and you want OpenAI-native tools, handoffs, guardrails, tracing, typed Python/TypeScript agent code, and direct integration with OpenAI platform workflows. For vendor-neutral products, keep business tools and state outside either SDK and make the provider-specific layer replaceable.