GUÍA Técnica

Agent2Agent (A2A) Protocol

The Agent2Agent (A2A) protocol is an open standard that lets AI agents built by different vendors on different frameworks find each other, describe what they can do, and hand tasks back and forth over ordinary web technologies.

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En esta pagina4 minutos de lectura
  1. Descripción general
  2. Buceo profundo
  3. Impacto Estratégico
  4. The Future of Agent2Agent (A2A) Protocol
  5. Implementación en el mundo real
  6. Riesgos y barandillas
  7. Hoja de ruta de implementación
  8. Sigue explorando
  9. Preguntas frecuentes

Descripción general

It complements the Model Context Protocol: MCP connects an agent to tools and data, while A2A connects an agent to other agents.

Buceo profundo

Google announced A2A in April 2025 with a large group of technology partners. The project was later contributed to the Linux Foundation so that it could be governed in the open. The protocol builds on familiar standards: HTTP for transport, JSON-RPC 2.0 for message structure, and Server-Sent Events for streaming updates. Discovery starts with an Agent Card, a JSON document that an agent usually publishes at a well-known URL. It gives the agent's name, a description, its service endpoint, the skills it offers, the input and output types it accepts, and how clients should authenticate. A client agent reads the card to decide whether this remote agent suits the job. Work is organized around tasks. A client sends a message made of parts, which can be text, files or structured data. The remote agent can create a task that moves through defined states such as submitted, working, input-required, completed, failed or canceled. Results come back as artifacts. For work that takes minutes or hours, the client can stream progress or register a webhook for push notifications instead of holding a connection open. A2A treats remote agents as opaque. The client does not see the other agent's prompts, tools, memory or model, only what it advertises and returns. Vendors can therefore cooperate without exposing their internals. People often assume A2A and MCP compete. They answer different questions. MCP describes how an agent calls tools and reads resources, which are usually well-defined functions with structured inputs and outputs. A2A describes how an agent works with another autonomous agent that has its own reasoning and may need several exchanges to finish. A single system can use both. Another misconception is that A2A handles trust on its own. It declares how to authenticate, but organizations still have to decide which agents to trust and what to share with them.

Impacto Estratégico

Costo y presupuesto

Las decisiones de arquitectura impulsan el rendimiento y los costos operativos durante años.

Decisiones más claras

La educación técnica ayuda a los equipos a elegir la pila adecuada, no sólo la más nueva.

control de calidad

Mejores opciones de ingeniería reducen los incidentes de confiabilidad en la producción.

The Future of Agent2Agent (A2A) Protocol

A2A is still relatively young, and its specification and SDKs have changed noticeably since launch. Adoption depends on whether enough vendors publish agents that are actually useful to call, and on whether registries and trust frameworks develop to help agents find reliable partners. Open questions include how to handle billing, reputation and accountability when one company's agent acts on another's instructions. It seems reasonable to expect A2A and MCP to be used side by side, while the details of how cross-organization agent networks will look in practice remain uncertain.

Implementación en el mundo real

A company's travel assistant finds a partner airline's booking agent by reading that agent's Agent Card, sees that it offers a 'rebook flight' skill, and sends it a task instead of scraping the airline's website.

A hiring coordinator agent passes candidate sourcing to one vendor's recruiting agent and background checks to another's. It tracks each as a separate A2A task with its own status.

A long-running research task sent to a specialist agent returns 'input-required' partway through. The client agent asks the user to clarify and sends the answer back on the same task.

Inside one agent, MCP connects it to a database and a file store. A2A is what that same agent uses to delegate a subtask to a separately owned agent whose inner workings it cannot see.

Riesgos y barandillas

  • La optimización de un punto de referencia puede ocultar debilidades más amplias del sistema.

  • Los costos de infraestructura y mantenimiento a menudo se subestiman.

  • Las brechas de seguridad y observabilidad pueden crecer a medida que los sistemas se vuelven más complejos.

Hoja de ruta de implementación

  1. Defina objetivos de latencia, calidad y costos antes de la implementación.

  2. Comparación en condiciones realistas de carga y datos.

  3. Monitoreo de instrumentos para detectar errores, deriva e impacto para el usuario.

  4. Prepare rutas de reversión y respuesta a incidentes antes de escalar.

Sigue explorando

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Preguntas frecuentes

What is Agent2Agent (A2A) Protocol?

The Agent2Agent (A2A) protocol is an open standard that lets AI agents built by different vendors on different frameworks find each other, describe what they can do, and hand tasks back and forth over ordinary web technologies. It complements the Model Context Protocol: MCP connects an agent to tools and data, while A2A connects an agent to other agents.

What is the main purpose of the A2A protocol?

A2A standardizes discovery and task exchange between independent agents, whoever built them.

How does A2A relate to MCP?

They solve different problems and can run in the same system: tool access through MCP and agent collaboration through A2A.

What is an Agent Card?

Client agents read the Agent Card to discover what a remote agent can do and how to connect to it.

Which standards does A2A build on?

A2A deliberately uses common web standards so it fits into existing infrastructure.

What does the 'input-required' task state mean?

The task pauses until the client sends a follow-up message on the same task, often after asking the user.