Agent-to-Agent Protocol (A2A)

The Universal Language for Multi-Agent Collaboration

Q: What is the Agent-to-Agent Protocol (A2A)?

A2A is an open, vendor-neutral protocol introduced by Google in 2025 that enables autonomous AI agents from different vendors, frameworks, and organizations to communicate, coordinate, and delegate work to one another using a common standard.

Q: How is A2A different from MCP?

MCP connects an individual agent to tools, data, and external systems (agent ↔ environment). A2A connects agents to each other (agent ↔ agent ↔ agent). They are complementary parts of the same stack and can be used together in multi-agent architectures.

Q: What standards does A2A use for communication?

A2A uses industry-standard HTTP(S) and JSON-RPC 2.0 for communication. Agents describe themselves via Agent Cards and then exchange structured task objects, messages, and artifacts over these standard protocols.

Q: Is A2A secure enough for enterprises?

Yes. A2A supports authentication via OpenID Connect, OAuth 2.0, and API keys; encrypted transport over HTTPS/gRPC; digitally signed Agent Cards; and reputation mechanisms so agents can avoid untrusted partners.

Q: Why should enterprises adopt A2A?

A2A lets you compose multi-agent systems without brittle, custom point-to-point integrations. It scales from a few agents to hundreds, allows mixing vendors and frameworks, and is backed by 50+ technology partners, making your architecture more future-proof.

A2A is an open protocol that lets autonomous AI agents from any vendor or framework discover each other, coordinate, and delegate work without custom integration code.

Introduced by Google in April 2025, A2A solves the agent silo problem by providing a standard way for agents to exchange tasks, messages, and artifacts unlocking truly collaborative multi-agent systems.

View A2A Spec

From Isolated Agents to Collaborative Teams

Today, most AI agents operate as silos. Each has its own framework (LangChain, CrewAI, AutoGen, custom Python), its own API conventions, and no standard way to discover or request work from other agents.

Building multi-agent systems typically means writing custom connectors and brittle middleware for every agent-to-agent interaction. Adding a new agent often requires yet another round of integration work.

A2A: A Standard for Agent Collaboration

A2A provides a vendor-neutral protocol so any agent can work with any other agent. Build agents using your preferred frameworks, deploy them anywhere, and let them collaborate via a shared language without per-integration glue code.

The Multi-Agent Problem

Each agent exposes its own proprietary API and data formats, making cross-vendor collaboration hard.
Integrations are point-to-point and brittle every new agent requires custom code.
Architectures become expensive to maintain and impossible to scale beyond a small number of agents.
Innovation slows down because every new agent or vendor integration is a multi-week project.

Architecture

A2A: Simplicity Built on Open Standards

A2A uses Agent Cards, structured task objects, and streaming messages over HTTP(S) and JSON-RPC 2.0 to coordinate complex multi-agent workflows.

Agent Cards

Agent Cards are public metadata files that describe what an agent can do, where it lives, and how to talk to it.

Capabilities and task types supported
Authentication requirements
Endpoints and protocol details
Organization identity and digital signatures

Messages, Streams & Artifacts

As tasks execute remotely, agents exchange rich information:

Streaming messages for progress updates and clarifications
Final artifacts containing structured outputs and files
Multi-modal payloads: text, JSON, documents, metadata

Under the hood, A2A uses HTTP(S) and JSON-RPC 2.0 no proprietary transport or gateway is required.

Task Objects & Delegation

Instead of raw function calls, A2A uses structured task objects:

Unique IDs for each task
Status tracking (pending, running, completed, failed)
Input payloads and options
Result delivery and error reporting

This enables deep chains of delegation where agents call other agents, which call others, while keeping workflows traceable.

Agent Autonomy

A2A keeps agents autonomous while enabling collaboration:

Agents decide which other agents to delegate to
Internal logic and models remain opaque and private
Trust can be guided by reputation signals
No single central orchestrator is required

Core Capabilities of A2A

A2A was designed from the ground up for long-running, collaborative, multi-modal agent workflows.

Task Objects & Formal Delegation

Define tasks with IDs, status, and structured inputs/outputs so agents can formally delegate and compose complex workflows without brittle middleware.

Long-Running Operations (LRO)

Support for tasks that run for minutes, hours, or days with asynchronous status tracking and streaming updates, so complex workflows never block and clients stay informed in real time.

Opaque Execution

Agents expose only their public contract via Agent Cards; internal logic, models, and prompts stay private, preserving IP and security.

Multi-Modal Communication

Exchange text, structured JSON, files, and metadata not just prompts enabling rich, enterprise-grade workflows.

Agent Autonomy

Each agent retains its own capabilities and decision-making while cooperating with others, enabling self-regulating networks of specialists.

Real-World Impact: What Becomes Possible

Multi-Stage Financial Workflows

Compliance, sanctions-checking, AML analysis, human review, and execution agents coordinate via A2A. Change workflows by reordering agents or adding new checks without rewriting integration code.

Autonomous Recruiting Pipelines

Resume parsing, skill extraction, job matching, scheduling, and feedback collection handled by specialized agents that can be swapped or re-ordered as hiring strategies evolve.

Scientific Investigation at Scale

Database-search, literature-analysis, simulation, and synthesis agents cooperate on complex research questions, with A2A coordinating multi-step reasoning.

Self-Healing Infrastructure

Monitoring agents detect anomalies, analysis agents propose fixes, remediation agents request approval and execute all speaking A2A.

24/7 Customer Service

Triage agents route to specialist agents, escalation agents coordinate with humans, feedback agents learn from interactions to continuously improve service quality.

A2A vs MCP: The Complete Agent Stack

A2A and the Model Context Protocol (MCP) are complementary not competing standards in the agent ecosystem.

MCP connects agents to tools and data (agent ↔ environment). A2A connects agents to each other (agent ↔ agent ↔ agent). Together they form the full stack for powerful, interoperable multi-agent systems.

MCP

Connects agents to tools, data, and external resources
Standardizes how agents access their environment
Ideal for plugging in APIs, databases, file systems, and UIs

A2A

Connects agents to each other across vendors and frameworks
Enables distributed teams of agents to coordinate
Supports task delegation, messaging, and artifacts between agents

Security & Trust Model

A2A was designed with enterprise-grade security: strong authentication, encrypted transport, verifiable identity, and decentralized reputation.

Authentication: OpenID Connect, OAuth 2.0, and API keys specified in Agent Cards.
Encryption: All communication over HTTPS/gRPC.
Digital Signatures: Agent Cards can be signed so clients can verify which organization created an agent before connecting.
Opaque Execution: Remote agent logic remains hidden; only the contract is visible.

Reputation & Self-Regulation

A2A includes concepts for reputation so agents can prefer reliable partners and naturally avoid bad actors.

Track success and failure rates for remote agents over time
Use reputation to route important tasks to trusted partners
Isolate unreliable agents without central gatekeepers

Ecosystem & Industry Adoption

A2A launched with 50+ technology partners including Google Cloud, Microsoft Azure, Atlassian, Box, PayPal, SAP, Stripe, and Twilio.

Proven deployments include Box AI Agents coordinating across dozens of platforms, Twilio using A2A for intelligent agent routing, and Microsoft Copilot Studio supporting A2A-based agent composition.

Google's Agent Development Kit (ADK) was built with A2A as its core protocol, signaling deep industry commitment and a likely path toward open governance (e.g., Linux Foundation stewardship).

Why GenAI Protos Builds on A2A

Our clients don't just need single agents they need coordinated teams of agents that can evolve over time without re-platforming.

1. Rapid Agent CompositionAssemble specialized agent teams quickly without custom integration for each pairing. A2A is framework-agnostic, so clients can choose their preferred tools.
2. Enterprise ScalabilityScale from two agents to fifty to hundreds without changing the underlying architecture. Different vendors and frameworks participate in the same workflows.
3. Future-ProofingWith 50+ partners and momentum toward open governance, A2A keeps multi-agent systems compatible as the ecosystem evolves.

For enterprises deploying multi-agent AI, A2A is the foundation that turns isolated, vendor-specific systems into coordinated, self-regulating agent teams.

Designing multi-agent systems and need A2A expertise?

We help you architect and implement A2A-based agent networks that coordinate reliably across vendors and platforms.

Agent-to-Agent Protocol (A2A) FAQ

Key questions about the A2A standard, how it compares to MCP, and how GenAI Protos uses it to build interoperable multi-agent systems.