Definition: Agent-to-Agent Protocol (A2A)
Agent-to-Agent Protocol (A2A) is an open, vendor-neutral standard that lets autonomous AI agents from different vendors discover each other’s capabilities through a published Agent Card and delegate, monitor, and complete multi-step tasks with one another over a common HTTP-based interface.
Core characteristics of Agent-to-Agent Protocol (A2A)
A2A standardizes horizontal communication between independent agents, in contrast to protocols that connect a single agent vertically to its tools. It was created by Google and is now governed by the Linux Foundation.
- Open standard under Linux Foundation governance, originally released by Google in April 2025
- Agent Card discovery: each A2A-compliant agent publishes a machine-readable card describing its skills and authentication requirements
- Task-based communication: agents exchange structured tasks with defined inputs, outputs, and status updates, not free-form chat
- Transport: JSON-RPC 2.0 over HTTP, with server-sent events for streaming updates on long-running tasks
Agent-to-Agent Protocol (A2A) vs. Model Context Protocol (MCP)
A2A and Model Context Protocol (MCP) solve different problems and are usually deployed together. MCP is vertical: it connects one agent to the tools and business systems it needs, with the agent acting as a client. A2A is horizontal: it connects one agent to another, potentially built by a different vendor in a different organization, so the two can hand off a task and report progress. A typical deployment uses MCP so each specialist agent can read and write to systems like an ERP, and A2A so those agents, or agents belonging to different companies, can delegate work without custom point-to-point integration.
Importance of Agent-to-Agent Protocol (A2A) in enterprise AI
A2A addresses a gap MCP does not: coordination between agents never designed to work together, including agents run by different companies in the same supply chain. It is what turns isolated agentic AI deployments into cooperating networks that cross company lines. By April 2026, one year after release, A2A had more than 150 supporting organizations and over 22,000 GitHub stars, with production use reported in supply chain, financial services, insurance, and IT operations (source: Linux Foundation, 2026).
Methods and procedures for Agent-to-Agent Protocol (A2A)
Deploying A2A follows three stages: publishing an Agent Card, exchanging tasks, and securing the connection.
Agent Card publication and discovery
Every agent reachable over A2A publishes an Agent Card, a JSON document describing what it can do, how to authenticate, and which task formats it accepts. Other agents fetch this card before initiating contact.
- Define the agent’s exposed skills and the input schema each skill expects
- Publish the card at a well-known endpoint so requesting agents can discover it automatically
- Version the card so downstream agents detect breaking changes before they cause failures
Task delegation and status streaming
Once an agent discovers a counterpart through its Agent Card, it sends a task request describing the desired outcome. The receiving agent can accept, reject, or ask clarifying questions, streaming status back over server-sent events for tasks lasting minutes or hours rather than seconds.
Security and identity verification between agents
Because A2A tasks often cross organizational boundaries, every request must carry verifiable agent identity and scoped authorization rather than a shared credential. Production deployments authenticate each call, log the requesting agent’s identity, and restrict which task types an external agent may request.
Important KPIs for Agent-to-Agent Protocol (A2A)
A2A deployments are measured across coordination reliability, adoption breadth, and task outcome quality.
Coordination reliability metrics
- Task acceptance rate: share of delegated tasks accepted without rejection (target: above 95%)
- Cross-agent handoff latency: time from delegation to first status update (target: under 2 seconds)
- Agent Card resolution success rate: share of discovery attempts that resolve a valid card (target: above 99%)
- Task completion rate without escalation to a human
Cross-vendor adoption breadth
Search interest in the protocol grew sharply through its first year, with queries for “A2A protocol” up 52% quarter-over-quarter by April 2026 (source: DataForSEO via Linux Foundation, 2026). Tracking how many partners and internal teams publish or consume Agent Cards shows how far coordination has moved from manual handoffs to protocol-based delegation.
Task outcome quality
Beyond completion, quality metrics track whether the outcome matched the requesting agent’s specification on the first attempt. A renegotiation rate above 10% typically signals that Agent Card skill descriptions need refinement.
Risk factors and controls for Agent-to-Agent Protocol (A2A)
A2A’s cross-organizational reach introduces risks that do not arise when all agents belong to one company.
Unauthorized cross-organization task delegation
An agent that accepts tasks from any requester without verifying identity and scope opens the door for a compromised or malicious external agent to trigger unintended actions.
- Maintain an allowlist of external agent identities permitted to delegate tasks, scoped by task type
- Require mutual authentication on every A2A session, not only at initial handshake
- Log every accepted and rejected task request for audit review
Protocol version fragmentation across partners
Because A2A is still maturing, partner organizations may run different protocol versions with incompatible task schemas. A silent mismatch is harder to catch than an outright failure, so Agent Card versioning and strict schema validation on both sides need periodic compatibility testing with key partners.
Opaque accountability across multi-hop delegation chains
When a task passes through several agents from different organizations before completion, tracing which agent made which decision requires coordinated logging across boundaries no single company controls end to end. This is a harder governance problem than internal multi-agent system auditing, and it needs contractual logging commitments between partners, not just technical controls on one side.
Practical example
A family-owned logistics company in North Rhine-Westphalia with 220 staff coordinates shipments across its own fleet-planning agent and the booking agents of three subcontracted carriers. Before A2A, each carrier integration meant a custom API connection maintained by a small IT team, and adding a subcontractor took four to six weeks. After each carrier published an A2A Agent Card describing its booking, capacity, and pricing skills, the logistics company’s agent could discover and delegate bookings to any compliant carrier agent without bespoke integration work.
- The fleet-planning agent checks live capacity across three carrier agents before assigning a shipment
- New carriers are onboarded by exchanging Agent Cards, cutting integration time from weeks to days
- Status updates on delayed shipments stream back automatically instead of manual check-in calls
- Exception handling routes disputed bookings to a human dispatcher with the full task history attached
Current developments and effects
A2A is consolidating its role as the coordination layer above agent-to-tool protocols like MCP.
A2A as the standard for cross-vendor agent coordination
The founding members that backed A2A at launch, including AWS, Cisco, Google, Microsoft, Salesforce, SAP, and ServiceNow, have continued shipping native support, with production use now reported across several industries.
- Microsoft has integrated A2A support into Azure AI Foundry and Copilot Studio
- AWS supports A2A through the Amazon Bedrock AgentCore Runtime
- Open-source orchestration frameworks are adding A2A adapters alongside existing MCP support
Convergence with MCP in production agent stacks
Enterprise teams building agent orchestration layers increasingly treat A2A and MCP as two halves of the same stack: MCP for each agent’s connection to internal systems, A2A for coordination between agents, internal or external.
Governance frameworks extending to cross-organization agent networks
Regulators that began by addressing single AI systems are extending scrutiny to networks of cooperating agents spanning company boundaries. Bitkom’s February 2026 guide on multi-agent systems in ERP contexts specifically addresses the interoperability question A2A answers, reflecting growing recognition that coordination standards, not just individual agent capability, will determine how fast Mittelstand companies automate cross-company processes (source: Bitkom, 2026).
Conclusion
Agent-to-Agent Protocol closes a coordination gap that agent-to-tool standards like MCP were never built to solve: letting agents from different vendors, and often from different companies, hand off work to each other reliably. For Mittelstand enterprises working with multiple software vendors and external partners, A2A reduces the custom integration work needed each time a new counterpart agent must be reached, extending workflow automation beyond a single company’s own systems. As cloud platforms ship native A2A support and orchestration frameworks treat it as a default alongside MCP, connecting an internal agent fleet to a partner’s agents keeps getting easier.
Frequently Asked Questions
What is the Agent-to-Agent Protocol (A2A) in simple terms?
A2A is a common language that lets AI agents built by different companies find each other, understand what each one can do, and hand off tasks to one another. Both sides implement the same open standard, similar to how email works between different providers regardless of which client either side uses.
How is A2A different from Model Context Protocol (MCP)?
MCP connects a single agent to the tools and data it needs, such as a CRM or database, in a client-server relationship. A2A connects one agent to another, potentially from a different vendor, so the two can coordinate a task together. Most production deployments use both: MCP inside each agent’s own system connections, A2A between agents that cooperate across organizational lines.
Does A2A make sense for a Mittelstand company with around 200 employees?
Yes, particularly if the company coordinates with multiple external vendors, logistics partners, or subcontractors whose systems already run AI agents. The relevant question is how many external counterparties the company’s own agents exchange tasks with; A2A pays off once that number exceeds one or two, since each new compliant counterpart requires no bespoke integration.
What does implementing A2A cost, and do we need our own IT resources?
Connecting to a partner that already publishes an A2A Agent Card requires configuration rather than custom development: registering the card, setting up authentication, and defining which task types your agent accepts or sends. Building your own Agent Card for an internal agent typically takes one to three weeks of developer time, similar in scope to building a custom MCP server.
How does A2A fit with DSGVO and the EU AI Act?
A2A is a communication protocol and does not remove the obligation to run a data protection assessment when tasks delegated between agents involve personal data crossing organizational boundaries. Under EU AI Act Article 14, oversight of high-risk agent decisions requires traceable logs; because A2A tasks can span multiple companies, contractual agreements on shared logging and audit access between partners are necessary alongside the protocol’s own authentication features.
How long does it take to get two organizations’ agents talking over A2A?
If both sides already run A2A-compliant agent frameworks, exchanging Agent Cards and agreeing on task schemas typically takes days rather than weeks. If one side needs to build A2A support into an existing agent from scratch, expect two to four weeks of development, comparable to a first MCP integration, with each subsequent partner connection getting faster once the internal Agent Card is in place.
