OpenAI Agents SDK vs Claude Agent SDK: An Honest Comparison

Both OpenAI and Anthropic ship official SDKs for building AI agents. If you’re starting a new agent project in 2026, you need to pick one (or use both). Neither is better in every situation. This post breaks down the differences.

OpenAI Agents SDK

OpenAI released their Agents SDK in March 2025. It’s a Python framework for building multi-agent systems.

Core concepts:

  • Agents. Each agent has a system prompt, a model, and a set of tools. You define agents as Python objects.
  • Handoffs. Agents can transfer control to other agents mid-conversation. A triage agent can route to a specialist agent based on the user’s request. This is the SDK’s standout pattern.
  • Guardrails. Built-in input and output validation. You can define rules that check agent responses before they reach the user. Useful for production systems where you need to catch bad outputs.
  • Tracing. Built-in observability with trace logging. You can inspect every step an agent took, which tools it called, and what it returned.

Strengths: The multi-agent handoff system is well designed. If you’re building something where different agents handle different domains (customer support with billing, technical, and sales agents), this is a natural fit. The guardrails system is mature. Python-first means a large ecosystem of compatible libraries.

Limitations: Python-only. If your stack is TypeScript or Go, you’re writing a separate service or finding a community port. Tightly coupled to OpenAI models. You can configure other providers, but the SDK is optimized for GPT models. The multi-agent patterns add complexity that simpler projects don’t need.

Claude Agent SDK

Anthropic’s approach is different. The Claude Agent SDK focuses on tool use and the model context protocol (MCP).

Core concepts:

  • Tool use. Claude models have strong native support for calling tools. You define tools with JSON schemas, and the model decides when and how to call them.
  • MCP integration. First-class support for MCP servers. Your agent can connect to any MCP-compatible tool provider and discover tools at runtime. No hardcoding tool definitions.
  • Extended thinking. Claude models can show their reasoning process, which helps with debugging and building trust in agent decisions.
  • Computer use. Claude can interact with desktop applications through screenshots and mouse/keyboard control. This is unique to the Anthropic ecosystem.

Strengths: MCP support means your agent’s capabilities can grow without code changes. Add a new MCP server, and your agent gains new tools automatically. The tool-use implementation is reliable, Claude models tend to call tools correctly with minimal prompt engineering. Extended thinking makes complex reasoning chains transparent.

Limitations: The multi-agent patterns aren’t as developed as OpenAI’s. If you need agent-to-agent handoffs, you’re building that yourself. The ecosystem is smaller. Computer use is impressive but slow and resource-heavy for production use cases.

Where They Overlap

Both SDKs handle the basics well: defining agents, connecting tools, running conversations with tool calls, and streaming responses. Both support structured outputs. Both have async execution patterns. For a single-agent system with a handful of tools, either SDK will work.

How to Choose

Pick OpenAI Agents SDK if:

  • You’re building a multi-agent system with clear routing between specialists
  • You need built-in guardrails for production safety
  • Your team writes Python and uses OpenAI models
  • You want mature tracing and observability out of the box

Pick Claude Agent SDK if:

  • Tool use is the core of your agent’s value
  • You want MCP-based tool discovery (connect once, get many tools)
  • You value transparent reasoning (extended thinking)
  • You need computer use capabilities

Use both if: You’re building a platform that supports multiple LLM providers. This is more common than you’d think. Many teams let users choose their preferred model.

AgentPatch Works with Both

AgentPatch is a tool provider, not a model provider. It doesn’t care which SDK you use.

If you’re using Claude Code or any MCP-compatible client, you connect AgentPatch as an MCP server and get access to all tools (web search, image generation, email, YouTube transcripts, Google Maps, and more) through one connection.

If you’re using the OpenAI Agents SDK, you can call AgentPatch tools through the REST API. Define each tool as a function in your agent, and have the function call the AgentPatch endpoint. The tools work the same regardless of which model calls them.

The value of a tool marketplace is that it decouples tool capabilities from model choice. You pick the best model for your use case. You pick the best tools for your use case. They don’t have to come from the same vendor.

Setup

Connect AgentPatch to your AI agent to get access to the tools:

Install the AgentPatch CLI (zero dependencies, Python 3.10+):

pip install agentpatch

Set your API key:

export AGENTPATCH_API_KEY=your_api_key

Then use it:

ap search "web search"
ap run agentpatch google-search --input '{"query": "test"}'

Get your API key from the AgentPatch dashboard.

Claude Code

Run this command to add AgentPatch as an MCP server:

claude mcp add -s user --transport http agentpatch https://agentpatch.ai/mcp \
  --header "Authorization: Bearer YOUR_API_KEY"

Replace YOUR_API_KEY with your actual key from the AgentPatch dashboard. Claude Code discovers all AgentPatch tools automatically.

OpenClaw

Add AgentPatch to ~/.openclaw/openclaw.json:

{
  "mcp": {
    "servers": {
      "agentpatch": {
        "transport": "streamable-http",
        "url": "https://agentpatch.ai/mcp",
        "headers": {
          "Authorization": "Bearer YOUR_API_KEY"
        }
      }
    }
  }
}

Replace YOUR_API_KEY with your actual key from the AgentPatch dashboard. Restart OpenClaw and it discovers all AgentPatch tools automatically.

Wrapping Up

The OpenAI Agents SDK and Claude Agent SDK solve similar problems with different priorities. OpenAI optimizes for multi-agent orchestration and safety rails. Anthropic optimizes for tool use and open protocols. The right choice depends on your specific project, not on which company you like more. Explore the tools available at agentpatch.ai to give either SDK access to capabilities beyond what ships built in.

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