WritingGuide
Google vs Anthropic for AI agents
The two stacks I choose between, layer by layer: managed platform, framework, models, hosting, access, integrations. Facts first; my view is marked as such.
I'm Matteo Gazzurelli, a fractional CTO and agentic AI consultant with MaGa Srl in Brescia. I compare these stacks against the systems, data and maintenance responsibilities of each project.
How to read this page
The Fact columns describe documented product capabilities as of October 2026. My view explains how I assess them for a client. Sources are linked beside the relevant claims.
The two sides are compared at the same level: a managed platform against a managed platform, a framework against a framework. Keeping the levels apart is what makes the comparison hold.
Layer by layer
| Layer | Anthropic | |
|---|---|---|
| Managed platform | FactGemini Enterprise Agent Platform: Agent Runtime to host agents, with Memory Bank, Agent Identity and Agent Gateway as managed components. | FactClaude Managed Agents (opens in a new tab): Anthropic runs the agent loop; tools execute in a sandbox per session, in Anthropic's cloud or self-hosted; agents are stored, versioned objects. Public beta since April 2026 (opens in a new tab), on by default for every API account. |
| My viewOn Google the platform is the whole production floor; on Anthropic it is the agent loop and its workspace. If you need identity and governance across several teams, start the evaluation from Google's side. | ||
| Framework | FactGoogle ADK (opens in a new tab): an open-source framework in Python, TypeScript, Go, Java and Kotlin. Defines agents, tools and workflows; can run on your infrastructure or on Google Cloud. | FactClaude Agent SDK (opens in a new tab): the harness behind Claude Code, as a library in Python and TypeScript. Built-in file and shell tools, MCP servers, sub-agents and hooks; runs on your infrastructure. |
| My viewI compare the tools, controls and deployment requirements on the same task. ADK can run outside Google Cloud; the Claude Agent SDK can connect to business systems through MCP. | ||
| Models | FactGemini models by default; ADK also runs models from other providers through LiteLLM. | FactClaude models are available on Google Cloud (opens in a new tab), Amazon Bedrock (opens in a new tab) and Microsoft Foundry. Claude Managed Agents (opens in a new tab) is a separate service, available through Anthropic's API and Claude Platform on AWS. |
| My viewI pick the model on the task with an eval set, after the platform question is settled. A model choice made before the platform choice tends to get reversed once the platform is chosen. | ||
| Hosting | FactADK can run on your own infrastructure (opens in a new tab). On Google Cloud, deployment options include Agent Runtime, Cloud Run and GKE. | FactClaude Managed Agents: sessions run in an Anthropic-managed sandbox or in a self-hosted one on your infrastructure (opens in a new tab). The Claude Agent SDK runs where you host it. |
| My viewThe hosting answer is usually already written in your cloud contract. I read that before I open either documentation. | ||
| Access and identity | FactGoogle Cloud IAM for people and service accounts; Agent Identity (opens in a new tab) gives each agent its own SPIFFE-based identity on Agent Runtime, Cloud Run and Gemini Enterprise, acting for itself or for an end user. | FactOrganization, workspaces (opens in a new tab) and roles in the Claude Console; API keys (opens in a new tab) tied to a person or a service account, or short-lived tokens from your identity provider. Tool credentials are supplied by your application per session. |
| My viewIf auditors ask who did what, Google's side answers with fewer custom pieces today. That gap can close; check the date at the top. | ||
| Integrations | FactMCP for tools, A2A (opens in a new tab) for agent-to-agent communication, both supported in ADK; the ADK documentation labels its A2A support experimental. | FactMCP for tools, built into the Agent SDK and available to Managed Agents (opens in a new tab). Agents call other agents through subagents in the SDK and multiagent orchestration (opens in a new tab) in Managed Agents. |
| My viewMCP is the layer that keeps the choice reversible: a tool written once serves both stacks. I start every integration there. | ||
Four questions that decide
Where do identity, logging and admin already live?
I check how each option connects to your existing identity, logging and administration. I estimate the integration work before comparing costs; where your systems run today is one input to that estimate.
Is the bottleneck the model, the tools or the process around people?
When the model is the bottleneck, I test Claude and Gemini on your cases before choosing a platform. When it is the tools or the process, the platform choice matters more than the model, and the eval set decides the model later.
Who runs it in six months?
Someone must own integrations, permissions, evaluation and incident handling. I check who can maintain each option. A managed platform reduces infrastructure work; it still needs technical ownership.
Can you mix Google and Anthropic?
Yes. Tools written for MCP serve agents on both sides, and A2A lets an ADK agent talk to an agent built elsewhere. A common shape is Google for identity and orchestration with a Claude model on the step where it tests best.
Related
- GuideGoogle ADK integration: evaluate, integrate, operate
- ServiceFractional CTO · The platform call, made with your team and written down.
- ServiceAI automation · Agents on a real process, on the stack that fits it.
- ArticleGoogle ADK in 2026: Where It Fits in Gemini Enterprise Agent Platform
Choosing for a real project?
Tell me which systems you run and what the agent should do. I'll say which pair fits your case, and why, before any build. A reply within 2 business days.
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