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Use A2A when one independently operated AI agent needs to discover, delegate work to, or exchange progress and results with another agent. Use MCP when an agent needs access to a tool, API, or resource. They solve different problems and can be used together: an agent might delegate analysis to a specialist through A2A while that specialist uses MCP to reach a search service or database.
This guide uses the A2A Project’s reviewed specification, version 1.0.0. Protocol documentation can change, so check the official specification and the behavior supported by your implementation before building against it.
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Choose the protocol by the relationship you need
A2A is an open standard for interoperability and collaboration between agents. The A2A Project describes its purpose as enabling “seamless communication and collaboration between AI agents.” MCP has a different role: it standardizes how agents connect to tools, APIs, and resources.
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|---|---|---|
| Communication relationship | Agent to agent | Agent to tool, API, or resource |
| Typical need | Discover a separate agent, delegate a task, and exchange progress or results | Expose or call a tool or data source |
| Core concepts in the reviewed documentation | Agent Card, Message, Part, Task, Artifact | MCP server and tool definitions or configuration |
| Implementation details to verify | Protocol version, binding, task and streaming behavior, authentication | Transport, server reachability, execution environment, credentials |
For example, handing a document to an independently built legal-review agent is an agent-to-agent delegation problem. Giving an agent access to a document repository is an agent-to-resource problem. A system can use both: the caller delegates with A2A, and an agent accesses its permitted repository through MCP.
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A2A is designed to let agents interact without requiring one to expose its internal memory, tools, or proprietary logic to the other. That design boundary is useful for interoperability, but it does not by itself secure a deployment or make a remote agent trustworthy.
Understand A2A’s structured objects
The A2A specification separates discovery, communication, stateful work, and outputs. Understanding these objects first makes it easier to design the caller and the remote agent as independently operated services.
Agent Card: discover the service and its capabilities
An Agent Card is JSON metadata describing an agent’s identity, capabilities, skills, endpoint, and authentication requirements. Use it to determine what a remote agent claims it can do and how to address it. Treat this metadata as a description, not proof that the agent is authorized for a particular request or that its claims are safe to rely on.
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Message and Part: represent a communication turn
A Message represents a turn in communication and includes a sender role and one or more Parts. A Part can carry text, a file reference, or structured data. This allows a request or reply to carry more than plain text while keeping the communication model explicit.
Task: track stateful work
A Task is a uniquely identified unit of work with status and potentially history and artifacts. The reviewed specification includes these task states:
- Submitted and working
- Completed, failed, canceled, or rejected
- Input required
- Authorization required
Design clients to handle the states they may receive rather than assuming that every request completes successfully in a single exchange. In particular, input-required and authorization-required outcomes need a defined caller action; treating them as ordinary completion can leave work stalled or permit an unsafe continuation.
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Artifact: carry the task’s output
An Artifact is output associated with a Task, such as a document, image, or structured data, and is composed of Parts. The specification distinguishes communication Messages from task outputs: use the Task and its Artifacts to represent results rather than treating every conversational message as a durable deliverable.
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A2A’s send operation can return either a direct Message or a tracked Task. A direct response fits an interaction that can finish in that exchange; a tracked Task fits work whose state and result need to be followed over time. The appropriate choice depends on the work and the behavior supported by the implementation.
- Discover the remote agent. Obtain and inspect its Agent Card, including its endpoint, declared skills, and authentication requirements.
- Send a bounded request. Specify the task, the information the agent needs, and the expected kind of output. Use structured Parts where they are more appropriate than prose.
- Handle the response type. If the operation returns a direct Message, process that response. If it returns a Task, retain its identifier and follow its status.
- Respond to intermediate states. Define what the caller does when work needs more input or authorization, and how it handles failure, rejection, or cancellation.
- Collect the result. Retrieve or process the completed Task’s Artifact rather than assuming a progress message is the final deliverable.
For longer-running work, the specification provides task status updates, streaming, push notifications, and task retrieval patterns. These are complementary ways to learn about progress; the client should select and implement the mechanisms its chosen binding and server support.
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- 【Real-Time Two-Way Communication】- Connect and converse hands-free with our unique design. No need to hold a button to talk and release to listen. Whether you're at home or in the office, our wireless room to room intercom ensures quick, easy, and effective communication. Enjoy a communication distance of approximately 1200 ft(in the open outdoor environment).
- 【Use in Different Places】- You can use our home intercom system in various places throughout your house, such as the bedroom, kitchen, living room, garage, and basement! Additionally, this full-duplex wireless intercom is perfect for use in offices, restaurants, back kitchens, hotels, reception areas, and more. The Hosmart intercom is designed to meet your multi-scene communication needs and serve as your reliable assistant.
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Plan for interrupted progress updates
Do not equate an open stream with durable delivery. The specification warns that a streaming client that reconnects may miss some status messages. If missing an update could affect correctness, design recovery around task retrieval and current task state instead of relying solely on replaying every streamed event. Treat ordinary Messages as communication, not as a guaranteed delivery channel for critical information.
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MCP is the appropriate boundary for giving an agent access to a tool, API, or resource; it is not a substitute for A2A’s agent-to-agent delegation model. An agent may use MCP to interact with a database or search service, while A2A connects that agent to a separate agent handling a specialist task.
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Connection details depend on the client and execution environment. OpenAI’s Agents API documentation describes three MCP connection choices for that product:
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- HTTP connections for servers reachable from OpenAI.
- Connections through an agent execution environment for servers on private networks or installed software.
- Stdio connections to a process in that execution environment.
OpenAI’s documentation also describes session credentials and reusable vault-backed credentials for applicable connections. These are OpenAI product options, not universal MCP requirements. The OpenAI Agents SDK documentation describes MCP server tools, hosted MCP tools, and configuration for preparing tool schemas; those are SDK-specific implementation choices, not a definition of every MCP client.
Design authentication and delegation boundaries
Protocol interoperability does not establish endpoint identity, grant least privilege, or validate an agent’s decisions. Treat each remote agent as an independently operated service and decide what it may do before sending it work.
The A2A specification supports explicit authentication requirements in Agent Cards and an authorization-required task state. It advises receiving credentials through a secure out-of-band channel, such as HTTPS, and warns that passing credentials in-band across an agent chain can expose them to participating agents. The protocol does not define the scope, validity, or revocation semantics of an authorization decision; your system must establish those policies.
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- Limit delegated authority. Give a remote agent only the access needed for its task. Do not assume that authorization for the caller automatically authorizes every downstream agent.
- Minimize shared information. Send only the input needed to complete the delegated work, and avoid placing reusable secrets in messages or task content.
- Validate inputs and outputs. Treat remote content and structured data as untrusted; validate formats and check that returned results are appropriate for the intended action.
- Require approval for sensitive actions. Define which actions need human or policy approval, and handle authorization-required outcomes explicitly.
- Define failure and cancellation behavior. Decide what happens when a task fails, is rejected, is canceled, or stops making progress, including whether dependent work should continue.
Pin and negotiate the protocol version
The reviewed A2A specification is version 1.0.0. Its versioning guidance identifies compatibility by major and minor version: clients must send the A2A-Version header, and servers must process the requested version or return a version-not-supported error.
Implement against a declared target version, and verify the version and binding supported by both sides. Do not assume that two A2A implementations expose identical behavior simply because both use the protocol name. Recheck the official specification when upgrading, especially where task states, streaming, or authentication behavior affects client logic.
Turn the model into an implementation plan
Before connecting independently implemented agents, write down the contract at each boundary. This makes protocol choices, task handling, and security policy reviewable rather than implicit.
Quick Recap
- Map relationships. Mark each connection as agent-to-agent (A2A) or agent-to-tool/resource (MCP). Use both when the workflow needs both relationships.
- Describe capabilities. For each A2A peer, decide what its Agent Card must communicate: identity, endpoint, skills, and authentication requirements.
- Define the task contract. Specify what information is sent, what kind of Artifact is expected, and which input, authorization, failure, rejection, and cancellation cases the caller handles.
- Choose progress handling. Decide whether the interaction is a direct Message or tracked Task. For longer work, select supported status, streaming, push-notification, or retrieval mechanisms and plan for interrupted connections.
- Constrain access. Set endpoint authentication, credential handling, least-privilege permissions, validation rules, and approval gates for sensitive actions.
- Test compatibility and recovery. Verify version negotiation and the target binding, then exercise disconnections and non-success task states so the caller does not depend on an uninterrupted happy path.
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