---
title: "Agent-to-Agent Protocol (A2A)"
id: "69786"
type: "page"
slug: "agent-to-agent-protocol-a2a"
published_at: "2026-10-05T13:55:16+00:00"
modified_at: "2026-10-05T13:55:16+00:00"
url: "https://www.uscloud.com/microsoft-support-glossary/agent-to-agent-protocol-a2a/"
markdown_url: "https://www.uscloud.com/microsoft-support-glossary/agent-to-agent-protocol-a2a.md"
---

Overview:

- [What is Agent-to-Agent Protocol (A2A) in Microsoft Foundry?](#what-is-agent-to-agent-protocol-a2a-in-microsoft-foundry)
- [How A2A interactions work](#how-a2a-interactions-work)
- [Where A2A fits in an agent architecture](#where-a2a-fits-in-an-agent-architecture)
- [A workplace example](#a-workplace-example)
- [Planning an A2A integration](#planning-an-a2a-integration)
- [Security and operational considerations](#security-and-operational-considerations)
- [A2A compared with tool calling](#a2a-compared-with-tool-calling)
- [Conclusion](#conclusion)
-

## What is Agent-to-Agent Protocol (A2A) in Microsoft Foundry?

Agent-to-Agent Protocol (A2A) is a way for independently built AI agents to communicate through a defined interface. One agent can describe its capabilities, receive a request from another agent, and return information or a task result. The goal is interoperability between agents, including agents developed with different frameworks or maintained by different teams.

In a Microsoft Foundry context, A2A is best understood as an architectural approach for connecting agents, not as a guarantee that every agent or Foundry configuration supports the same functions. The exact integration depends on the protocol implementation, the agents involved, and the platform capabilities available in a given environment.

## How A2A interactions work

An A2A exchange typically begins when a requesting agent identifies a suitable agent and sends it a task. The receiving agent interprets the request, performs work within its own capabilities and permissions, and returns a response or task status. Depending on the implementation, the exchange may be synchronous or may involve a longer-running task with subsequent status checks.

The agents remain distinct components. They may have different instructions, tools, data connections, owners, and security boundaries. A protocol can standardize how they exchange messages, but it does not make their underlying data, reasoning, or permissions equivalent.

## Where A2A fits in an agent architecture

A2A is useful when a workflow needs collaboration between separately scoped agents. For example, one agent may coordinate a request while other agents handle domain-specific tasks.

- **Agent-to-agent communication:** Agents exchange tasks and results through a defined interface.
- **Tool calling:** An agent invokes a function, API, or other tool to perform a specific operation.
- **Human interaction:** A person provides direction, reviews outputs, or approves consequential actions.

These patterns can coexist. An agent might use tools to gather information, call another agent for specialized analysis, and present a combined result to a person.

## A workplace example

Consider an internal service desk workflow in which a coordination agent receives a request to investigate a failed employee onboarding. It could ask a directory-focused agent to check account-provisioning status and a device-focused agent to report whether a managed computer has been assigned. The coordination agent then assembles the responses for a support specialist.

This design can separate responsibilities, but the returned information is only as dependable as each agent’s data access, instructions, and error handling. The workflow should also make clear which agent supplied each result and whether a human must verify it before any account or device changes are made.

## Planning an A2A integration

A practical integration process can help teams establish clear boundaries before connecting agents:

1. **Define the workflow.** Identify the business task, expected result, and decisions that remain with a person.
2. **Assign agent responsibilities.** Specify what each agent may do, what information it needs, and what it must not do.
3. **Agree on the interaction contract.** Define request and response formats, task status behavior, error handling, and any capability-discovery mechanism used by the implementation.
4. **Set identity and authorization boundaries.** Determine how agents are authenticated and which resources each agent may access.
5. **Test expected and failure cases.** Include incomplete requests, unavailable agents, invalid responses, timeouts, and attempts to exceed permissions.
6. **Monitor and revise.** Review task outcomes and operational signals, then adjust the workflow, controls, or agent responsibilities as needed.

## Security and operational considerations

A2A introduces an additional communication boundary. A connected agent may receive sensitive context or produce output that influences another agent’s decisions. Teams should treat agent requests and responses as data that require validation, access controls, and appropriate monitoring.

Important considerations include:

- **Least privilege:** Give each agent only the access required for its assigned role.
- **Input and output validation:** Do not assume that requests or responses are complete, safe, or accurate merely because they came from another agent.
- **Data handling:** Decide what information may be shared between agents, and how it should be logged or retained.
- **Failure behavior:** Define what happens when an agent is unavailable, returns an error, or produces an inconclusive result.
- **Human oversight:** Require review or approval where an agent’s response could trigger a consequential business action.

Implementation details and available controls may vary by protocol implementation, product version, tenant configuration, and service updates.

## A2A compared with tool calling

Tool calling gives an agent a way to invoke a specific function or service, such as retrieving a record or submitting a structured request. A2A instead connects agents as participants that can handle tasks within their own defined capabilities. In practice, an agent may use both: a tool to access a system and A2A to delegate a specialized task to another agent.

The distinction matters when designing responsibility and governance. A narrowly defined tool can make an operation explicit, while agent-to-agent delegation can accommodate a broader task but may add uncertainty about how the receiving agent interprets the request. Teams should choose the interaction pattern that matches the task, permissions, and oversight requirements.

## Conclusion

A2A provides a structured way for distinct AI agents to exchange tasks and results. In a Microsoft Foundry setting, it can be considered as one possible pattern for composing agent-based workflows, while specific support and behavior depend on the environment and implementation.

Successful use requires more than connecting endpoints. Teams need clear agent roles, a well-defined interaction contract, appropriate identity and data controls, failure handling, and human review where business decisions warrant it.