Quick Verdict
Bottom Line
Claude Agent SDK is the right choice if your agent needs to operate a computer: read files, run shell commands, edit code, browse the web. It ships with 8 built-in tools and the same agent loop powering Claude Code. OpenAI Agents SDK is the right choice if your agent needs to coordinate multiple specialists: route conversations, validate inputs/outputs, and hand off between domain-specific agents. It ships with tracing, guardrails, and voice agent support.
Architecture Comparison
The deepest difference is what each SDK assumes an agent is. Claude Agent SDK treats an agent as an autonomous operator with direct access to your environment. OpenAI Agents SDK treats an agent as a coordinator that delegates work to specialized sub-agents.
| Feature | Claude Agent SDK | OpenAI Agents SDK |
|---|---|---|
| Release date | September 2025 | March 2025 |
| Core abstraction | Agent loop with hooks | Agents + Handoffs + Guardrails |
| Built-in tools | 8 (Read, Write, Edit, Bash, Glob, Grep, WebSearch, WebFetch) | Hosted (web search, file search, code interpreter) |
| MCP support | Native (local, HTTP, in-process) | Yes (stdio, HTTP transports) |
| Multi-agent | Subagents (parallel execution) | Handoffs (conversation transfer) |
| Guardrails | Hooks (PreToolUse, PostToolUse) | Dedicated guardrail primitives |
| Tracing | Via hooks | Built-in dashboard |
| Voice agents | No | Yes (Realtime API) |
| Context management | Auto-compaction (200K+ token sessions) | Sessions (conversation history) |
| Cost controls | max_budget_usd, max_turns | Token limits per agent |
| Extended thinking | Yes (chain-of-thought blocks) | No (o-series reasoning is internal) |
| Skills/Plugins | Agent Skills (filesystem-based) | Custom function tools |
| Provider lock-in | Claude models only | Provider-agnostic (100+ LLMs) |
| Python package | claude-agent-sdk | openai-agents |
| TypeScript package | @anthropic-ai/claude-agent-sdk | @openai/agents |
Claude Agent SDK: The Operator
The SDK extracts Claude Code's agent loop into a library. Your agent gets the same lifecycle: gather context, take action, verify work, repeat. Hooks fire at every step (PreToolUse, PostToolUse, SubagentStart, Stop, PermissionRequest), giving you programmatic control over what the agent can do. Built-in tools mean your agent can read files, run shell commands, and edit code without you writing any tool implementations.
OpenAI Agents SDK: The Coordinator
Born as a production successor to Swarm, the SDK gives you three primitives: Agents (LLMs with instructions and tools), Handoffs (conversation transfer between specialists), and Guardrails (input/output validation that runs in parallel). Built-in tracing captures every LLM call, tool invocation, and handoff for debugging and evaluation. The Realtime API adds voice agents with interruption detection.
Tool Calling and MCP
Both SDKs support custom function tools and MCP (Model Context Protocol) servers. The difference is in what ships out of the box and how tools get validated.
Claude Agent SDK: Built-in Tools + MCP
The 8 built-in tools cover most coding agent workflows without writing a single tool definition. Read and Grep handle code understanding. Edit handles modifications. Bash runs tests and commands. WebSearch and WebFetch handle research. MCP servers extend this further: connect to Slack, GitHub, databases, or any service with an MCP implementation. Tools require explicit permission before Claude can use them, controlled through the allowed_tools configuration.
OpenAI Agents SDK: Function Tools + Hosted Tools + MCP
OpenAI offers three categories. Function tools are your custom implementations. Hosted tools (web search, file search, code interpreter) run on OpenAI infrastructure, so you don't manage execution environments. MCP tools connect to external servers via stdio or HTTP. Guardrails validate tool inputs and outputs in parallel with execution, catching issues before they propagate.
MCP: The Common Ground
Both SDKs support MCP, which means any MCP server you build works with either framework. Anthropic created MCP and has deeper native integration, but OpenAI's adoption means your tool investments are portable across both ecosystems. Google ADK also supports MCP, making it a genuinely cross-framework standard.
Multi-Agent Support
Both SDKs support multi-agent patterns but model them differently.
Claude: Subagents
Subagents are separate agent instances your main agent spawns for focused subtasks. They run in isolated contexts with their own instructions and tool permissions. Multiple subagents execute concurrently, so a code review agent can run style-checking, security scanning, and test coverage analysis in parallel. The parent agent aggregates results. Think of it as fork/join parallelism for AI tasks.
OpenAI: Handoffs
Handoffs transfer the entire conversation from one agent to another. A triage agent receives a request, identifies the domain, and hands off to a billing agent, tech support agent, or sales agent. The receiving agent picks up the full context. Two patterns: Manager mode (central agent invokes specialists as tools) and Handoff mode (agent transfers conversation ownership entirely).
The architectural difference matters. Claude's subagents are best for parallel execution of independent subtasks within a single workflow. OpenAI's handoffs are best for sequential routing across domain-specific agents in a conversation. If your use case is "analyze this codebase from five angles simultaneously," subagents fit. If it's "route this customer to the right department," handoffs fit.
Language SDKs
| Language | Claude Agent SDK | OpenAI Agents SDK |
|---|---|---|
| Python | claude-agent-sdk (PyPI, Python 3.10+) | openai-agents (PyPI, ~14.7M downloads/month) |
| TypeScript | @anthropic-ai/claude-agent-sdk (npm) | @openai/agents (npm, ~1.5M downloads/month) |
| Go | Community (unofficial) | No |
| Java | No | No |
| Feature parity | Python-first, TS close behind | Python-first, TS close behind |
Both SDKs follow the same pattern: Python gets features first, TypeScript follows within weeks. OpenAI's TypeScript SDK launched in July 2025, four months after the Python version. Claude's TypeScript SDK launched alongside the Python SDK in September 2025. Both TypeScript SDKs now have near-complete feature parity with their Python counterparts.
OpenAI has a significant install-base lead: 14.7M monthly Python downloads vs Claude Agent SDK's smaller but rapidly growing user base (backed by Claude Code's 84K+ GitHub stars). For TypeScript, OpenAI sees about 1.5M monthly downloads.
Pricing
Both SDKs are free. You pay for the model API calls your agents make. The cost difference depends on which models you use and how aggressively you optimize.
| Model | Input / 1M tokens | Output / 1M tokens |
|---|---|---|
| Claude Sonnet 4.6 | $3.00 | $15.00 |
| Claude Opus 4.6 | $5.00 | $25.00 |
| Claude Haiku 4.5 | $1.00 | $5.00 |
| GPT-4o | $2.50 | $10.00 |
| GPT-5.2 | $1.75 | $14.00 |
| o3 (reasoning) | $2.00 | $8.00 |
| GPT-4o-mini | $0.15 | $0.60 |
Cost Optimization
Claude Agent SDK offers max_budget_usd to cap spending per agent run and prompt caching for 90% savings on repeated context. OpenAI offers cached input pricing at 50% off and Batch API for 50% off asynchronous workloads. Both support combining caching with batching for significant savings on high-volume agent deployments.
Claude Agent SDK's context compaction also saves money indirectly. Instead of failing when the context window fills up, it automatically summarizes previous messages, letting long-running agents continue without restarting (and re-sending) the full context.
When to Choose Each
Choose Claude Agent SDK When...
Your agent operates a computer: reads code, edits files, runs tests, browses documentation. You want built-in tools that work immediately without writing tool definitions. You need subagents for parallel subtask execution. You're building developer tools, CI/CD automation, code review bots, or research agents that interact with the filesystem. You want the same runtime that powers Claude Code.
Choose OpenAI Agents SDK When...
Your agent coordinates conversations: routes requests to specialists, validates inputs/outputs, and hands off between domains. You need built-in tracing and a debugging dashboard. You want voice agent capabilities via the Realtime API. You're building customer support systems, sales pipelines, or multi-domain chatbots. You want provider flexibility to swap models without rewriting agent logic.
The Overlap Zone
Both SDKs can technically do what the other does. You can add file tools to OpenAI agents. You can build handoff patterns with Claude subagents. The question is where each SDK applies its engineering effort. Claude Agent SDK is optimized for the "give the agent a computer" paradigm. OpenAI Agents SDK is optimized for the "build a team of specialists" paradigm. Working with the grain of each SDK is faster than fighting against it.
Google ADK: The Third Option
Google's Agent Development Kit deserves mention for teams evaluating all three options. Released April 2025, ADK takes a different approach: enterprise-grade multi-agent orchestration with deep Google Cloud integration.
A2A Protocol
Agent-to-Agent protocol enables agents built on different frameworks (ADK, LangGraph, CrewAI) to communicate. Version 0.2 adds stateless interactions and standardized authentication. No other SDK has cross-framework agent communication.
Model-Agnostic
ADK supports Gemini, Claude, Llama, and other models via Vertex AI and LiteLLM. Unlike Claude Agent SDK (Claude-only) and OpenAI Agents SDK (optimized for OpenAI), ADK doesn't privilege any single provider.
Multi-Language
ADK supports Python, Java, and Go. This is the broadest language support of the three. For Java-heavy enterprise teams, ADK is currently the only option with first-party support.
ADK's tradeoff: it's more complex than either Claude or OpenAI's SDK and optimized for Google Cloud deployments. If you're already on Vertex AI, ADK is a natural fit. If you're not, the cloud dependency adds friction.
The Infrastructure Layer: What Every Agent SDK Needs
Agent SDKs handle the loop: receive a prompt, call tools, process results, repeat. But the quality of what happens inside each tool call determines whether your agent succeeds or spins.
A coding agent using Claude Agent SDK's built-in Edit tool is limited by how fast and accurately that tool applies changes. A research agent using OpenAI's hosted code interpreter is limited by the execution environment. Every agent is limited by how well it can search the codebase it's working in.
This is the layer Morph operates at. Not the agent loop, not the model, but the infrastructure primitives that agents call:
Fast Apply
Code edit operations at 10,500 tok/s. When your agent generates a diff, Fast Apply merges it into the source file. Works with any SDK's edit tool or as a standalone API. The difference between an agent that edits 3 files per minute and 30.
Agentic Code Search
WarpGrep runs 8 parallel tool calls per turn across 4 turns in under 6 seconds. Coding agents spend 60% of their time searching for relevant code. Faster, more accurate search means fewer wasted tokens and more first-attempt correct edits.
SDK-Agnostic
Morph's APIs work with Claude Agent SDK, OpenAI Agents SDK, Google ADK, LangGraph, or raw API calls. The infrastructure layer doesn't care which agent loop sits above it. MCP server support means any MCP-compatible SDK can use these tools natively.
Frequently Asked Questions
What is the difference between Claude Agent SDK and OpenAI Agents SDK?
Claude Agent SDK is a local runtime with 8 built-in tools (Read, Write, Edit, Bash, Glob, Grep, WebSearch, WebFetch) and hooks for lifecycle control. It's the same agent loop powering Claude Code. OpenAI Agents SDK is an orchestration framework with three primitives (Agents, Handoffs, Guardrails) and built-in tracing. Claude gives your agent a computer. OpenAI gives your agent a team.
Do both SDKs support MCP?
Yes. Both support Model Context Protocol servers for external tool integration. Claude Agent SDK has native MCP support with local, HTTP, and in-process transports. OpenAI Agents SDK supports stdio and HTTP transports. Any MCP server you build works with either SDK, making your tool investments portable.
Which SDK supports TypeScript and Python?
Both. Install claude-agent-sdk (Python) or @anthropic-ai/claude-agent-sdk (TypeScript) for Claude. Install openai-agents (Python) or @openai/agents (TypeScript) for OpenAI. Python gets features first in both ecosystems, with TypeScript following within weeks.
How does pricing compare?
Both SDKs are free. Model costs: Claude Sonnet 4.6 is $3/$15 per million tokens (input/output). GPT-4o is $2.50/$10. Claude Opus 4.6 is $5/$25. o3 is $2/$8. Claude offers 90% savings via prompt caching. OpenAI offers 50% cached input pricing. Both offer 50% batch discounts. Claude Agent SDK adds max_budget_usd for hard spend caps per agent run.
Is Claude Agent SDK the same as Claude Code?
The Agent SDK extracts Claude Code's agent loop into a library. Claude Code is the full terminal-based coding tool. The SDK gives you the same tools, context compaction, subagent support, and lifecycle hooks, programmable in Python and TypeScript. Think of Claude Code as a product built on the Agent SDK.
Does OpenAI Agents SDK work with non-OpenAI models?
Yes. It's provider-agnostic and supports any model with a Chat Completions API, including Claude, Gemini, DeepSeek, and Llama. OpenAI models get the deepest integration (Realtime API, hosted tools), but the core agent loop works with 100+ providers.
What about Google ADK?
Google ADK is a third option focused on enterprise multi-agent systems. It supports Python, Java, and Go. The A2A protocol enables agents from different frameworks to communicate. It's model-agnostic via Vertex AI. Best for teams already on Google Cloud who need cross-framework agent interoperability.
Which SDK is better for building coding agents?
Claude Agent SDK has a structural advantage. It ships with file operations (Read, Write, Edit, Glob, Grep), shell execution (Bash), and auto-compaction for long-running sessions. It's the same runtime behind Claude Code, which 71% of developers using AI agents rely on. OpenAI Agents SDK requires custom tool implementations for file operations but offers more flexibility in structuring multi-agent coding workflows. For the infrastructure layer (fast code edits, code search), see Morph Fast Apply and WarpGrep.
Related Comparisons
Build the Infrastructure Layer with Morph
Both Claude Agent SDK and OpenAI Agents SDK need fast code edits and accurate code search underneath. Morph provides these primitives as APIs and MCP servers that work with any agent framework. 10,500 tok/s Fast Apply. 8-parallel-call agentic search. SDK-agnostic.