Agent2Agent protocol: connect AI agents without losing control

What is the Agent2Agent protocol, and what problem does it solve?

Agent2Agent, often called A2A, is an open protocol for communication between independent AI agents. Its official specification describes a common model for discovering another agent, understanding its capabilities, exchanging messages, and managing a task without exposing the other agent's private memory, tools, or implementation.

Consider a workflow in which one agent checks product facts, another prepares a support summary, and a third routes it to a person. Custom connections between every pair are difficult to maintain or replace. A shared protocol can reduce that work, but the business still has to check the request, the freshness of the data, and whether the answer is suitable to send.

The protocol became a Growth Stage project in the Agentic AI Foundation on August 27, 2026. That status signals active development and community investment. It does not turn support claims into a procurement shortcut. Test the version, the available interfaces, the authentication design, and the failure behavior in the environment your team will run.

How is A2A different from a tool connection?

A2A describes a handoff between peers. One agent discovers another, checks its stated capabilities, sends a task, follows its progress, and collects the result. Like delegating a defined job, the requester needs to understand the assignment and outcome without knowing every internal step.

A tool connection is a different boundary. Tools let an agent call a service, database, or business system. The A2A project describes the Model Context Protocol as a way to connect agents to tools and data, while A2A connects one agent to another. A workflow may use both. Keep the authority model explicit: a handoff should not let an agent bypass the access checks that protect the tool or the business record.

For example, a customer service agent could send a structured research request to a knowledge agent. The knowledge agent can return candidate answers with source links and confidence notes. The service agent can then present the result to a human reviewer. Neither agent should silently change a subscription, issue a refund, or make a delivery promise because the handoff succeeded.

What should an agent card tell your team before it connects?

An Agent Card is the A2A description that helps another agent decide whether a connection makes sense. The current documentation lists identity, service endpoint, supported capabilities, authentication requirements, and skills among its key elements. Treat that document as a starting point for technical discovery, not a grant of trust.

Before your team allows a connection, ask five plain questions. Who operates this agent? Which skill will receive the task? What data does it need? Which identity and authorization method protects the connection? Where does the work stop for review? If the card exposes a sensitive internal endpoint or a skill description that should stay private, use an authenticated extended card or a protected discovery path. Do not put a secret inside the public card.

The A2A documentation also recommends standard caching controls for cards that change infrequently. That makes stale capability information an operational concern. Assign an owner, version the capability record, and test what happens when a skill, endpoint, or authorization requirement changes.

Which first A2A handoff gives a business useful proof?

Start with a small task that has a clear beginning, a structured result, and low consequences if it fails. A service business might ask a knowledge agent to assemble current service area and policy facts for a support person. An ecommerce team might request a product fact check that compares the selected offer with an approved catalog record. A product team might route a bug report to a diagnostic agent that returns a summary and linked evidence for an engineer.

Avoid starting with actions that create an irreversible customer result. Bookings, refunds, price changes, account access, and payment steps need the business rules that already govern those actions. An agent handoff can prepare information for that decision. It should not become a hidden path around consent, authentication, spend limits, or approval.

The current A2A task model provides states such as working, input required, authentication required, completed, canceled, rejected, and failed. Build your user and operator experience around those interruptions. A request that needs more customer information should ask for it clearly. A request that cannot authenticate should say so without exposing secrets. A failed task should preserve the context a person needs to finish or repair the work.

How should teams test an A2A connection before more authority is added?

Run a defined scenario through the whole path. Begin with a known request and approved source record. Verify that the requesting agent discovers the intended card, sends only the necessary context, and receives a status trail that matches what the receiving agent did. Make the task request missing information, require authentication, return a stale fact, and fail halfway through. Each case should have a safe response.

Follow the task through to the reviewer. They should be able to inspect the source record and task history, explain the outcome, cancel the work, or have the right owner correct a fact and rerun it. Test those recovery steps before relying on the connection.

NIST's AI Risk Management Framework organizes risk work around govern, map, measure, and manage. It is not a product checklist, but the framing helps here. Govern by naming decision owners. Map the handoff and its consequences. Measure the errors, blocked tasks, review load, and recovery time. Manage by changing the workflow or reducing authority when the evidence shows a risk.

Can A2A improve SEO, AEO, or GEO visibility?

Only indirectly, and no protocol connection guarantees crawling, indexing, AI citations, traffic, leads, sales, or revenue. A2A can help a team maintain the internal work that supports better public information: approved product facts, reviewed support answers, current service pages, and source records with clear owners. The public page still needs useful text, accurate structured data that matches visible content, crawl access, internal links, and a good user experience.

Google Search Central says its AI features use the same foundational requirements as Search. A page must be indexed and eligible to appear with a snippet to be eligible as a supporting link, and Google does not require special files or special schema for AI Overviews or AI Mode. Treat A2A as an operations choice, not an AI visibility trick.

For citation readiness, think beyond your own article. A brand needs claims that agree across current public pages, technical documentation, support material, partner records, reputable directories, and authentic customer reviews where those sources apply. An internal agent handoff can help spot inconsistencies. It cannot manufacture independent corroboration or make an unsupported claim trustworthy.

Frequently asked questions about the Agent2Agent protocol

Is A2A ready for every business workflow?

No. The protocol has an active specification, SDKs, and community momentum, but each team must verify the version, interface support, authentication approach, operational reliability, and business fit. Start with a bounded handoff and expand only after the evidence supports it.

Does an Agent Card reveal an agent's private memory or tools?

No. The protocol is designed for agents to describe capabilities and collaborate without exposing internal state, memory, or tools. The card can still contain sensitive endpoint or skill information, so protect sensitive detail with authenticated discovery and authorization controls.

Should an A2A task be allowed to complete a purchase or change an account?

Only if the business has independently designed and tested the required identity, consent, payment, policy, approval, logging, and recovery controls. A successful task handoff does not prove a customer commitment is authorized or correct.

Related Deploy Agentic guides

Use the AI agent data boundaries guide to set limits for reading, retaining, changing, and sending data. The agent operations scorecard helps teams measure review load, blocked actions, and cleanup before they grant more authority. Read the MCP server governance guide for tool policy and response inspection, then browse the Deploy Agentic blog, see the systems in our ecosystem, or review our approach to engineering.

Sources

• A2A Protocol: official specification version 0.3.0, reviewed August 30, 2026.
• A2A Protocol: Agent Discovery and Agent Cards, reviewed August 30, 2026.
• A2A Protocol: joining the Agentic AI Foundation, August 27, 2026.
• NIST: Artificial Intelligence Risk Management Framework 1.0, reviewed August 30, 2026.
• Google Search Central: AI features and your website, reviewed August 30, 2026.