[KongchangAI]
ConceptA2A协议 / Agent-to-Agent / A2UI

A2A

Agent-to-Agent (A2A) is a communication protocol for multi-agent system collaboration, designed to standardize task delegation, information exchange, and coordinated execution between AI agents. The protocol defines standard interfaces and message formats for inter-agent interaction, enabling heterogeneous agents to discover one another and collaborate across platforms and frameworks. It is typically used alongside tool-calling protocols such as MCP to form the foundational communication layer of multi-agent applications.

Core Facts

Timeline (last 90 days)

Oct 22

A developer shared on Reddit their experience building a PoC bridging MCP and A2A, concluding that interoperability is much harder than it looks: although the basic link worked, problems at the semantic level were prominent.

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Oct 22

Advice for teams planning similar MCP-A2A bridging: first assess the feasibility of semantic alignment before writing the adaptation layer; factor state management complexity into schedule estimates; and design a traceable logging strategy for error translation.

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Oct 22

The cost of protocol interoperability often lies not in the protocol specification itself but in the semantic gaps the specification does not cover; standards organizations can define message formats, yet it is very difficult to define the mapping rules between two protocols' conceptual models.

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Oct 22

When bridging MCP and A2A, the bridge layer needs to map A2A's Task state machine into intermediate states that the MCP caller can understand and handle the case where tasks continue running in the background after the session disconnects, which requires the bridge to persist a task mapping table and implement polling or push forwarding.

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Oct 22

A2A's task model is designed for long-running scenarios: a task delegation produces a Task object with a unique ID whose state transitions among submitted, working, input-required, completed, failed and others, during which progress updates can be streamed via SSE, and push notification callbacks are also supported.

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Oct 22

MCP's tool schema requires field-by-field definition of types and constraints, and the calling model generates structured parameters accordingly; the A2A side lacks equivalent formal information, so the adaptation layer can only rely on inference or manually supplementing the schema.

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Oct 20

Step X directly calls the MCP and A2A interfaces exposed by applications, completing cross-application interactions in script form, reducing recognition errors and the risk of being blocked.

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Oct 20

In the demo, when no policy was configured, the assistant's request for exchange rates received a 403 Forbidden; after configuring a TBAC policy that only allows access to the GetCurrencyExchangeRate tool, the query returned to normal; the exchange succeeded after two additional policies were added; and after it was marked as requiring approval, human-in-the-loop was triggered, with a push notification sent to the mobile device requiring allow or deny within 60 seconds, with automatic denial on timeout.

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Oct 20

When multiple protocols coexist, a unified gateway and observability design are needed, with attention to identity authentication, task idempotency, timeouts, and failure fallback.

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Oct 19

When an MCP tool fails, returning a structured error (such as one containing error and detail fields) is more effective than throwing an exception that becomes a generic error message, and more capable models will self-recover based on detail.

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40 more timeline events

All Facts (20)

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A2A (Agent-to-Agent) is an inter-agent communication protocol proposed by Google.

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A2A introduces the concept of an Agent Card, where each Agent publishes a structured capability declaration document describing the task types it can handle, input/output formats, and authentication requirements.

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The MCP protocol uses JSON-RPC 2.0 as its underlying communication protocol and defines three core primitives: Resources, Tools, and Prompts.

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The A2A protocol focuses on peer-to-peer collaboration between agents, while Anthropic's MCP focuses on connecting agents to tools and data sources.

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Google released the A2A (Agent-to-Agent) protocol in April 2025, specifically to address collaboration issues in multi-agent systems.

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The A2A (Agent-to-Agent) protocol manages collaboration between Agents, addressing issues of capability discovery, task delegation, and collaborative interoperability.

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MCP addresses the connectivity problem (how a model reaches tools), while Skill addresses the usage problem (when and with what strategy the model combines tools).

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An Agent Card is a standardized business card for agents in the A2A protocol, declaring capabilities, input/output schemas, authentication methods, and other information in JSON format, without exposing the internal model and tool implementations.

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The core design principle of the A2A protocol is that agents collaborate based on declared capabilities rather than inspecting each other's internal implementations.

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The core working unit of the A2A protocol is a Task, which has a unique ID and a complete state machine, including states such as submitted, working, completed, failed, canceled, and requires additional information.

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Protobuf is a language-neutral, platform-neutral structured data serialization protocol developed by Google, offering smaller data size and faster parsing speed compared to JSON and XML.

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文章介绍的六大AI智能体协议为MCP、A2A、UCP、AP2、A2UI和AGUI

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A2A协议通过Agent Card让每个Agent暴露能力清单,实现Agent之间零代码、零API契约的即插即用连接

90%
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Google创建了A2A(Agent-to-Agent)协议并将其捐赠给Linux基金会

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A2A协议的传输层使用JSON-RPC 2.0走HTTPS,长任务用Server-Sent Events做流式更新或Webhook做异步通知,版本0.3还加了gRPC支持

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A2A协议基于HTTP/SSE构建,引入了Agent Card概念,每个Agent发布描述自身能力的元数据卡片

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A2A和MCP是互补关系而非竞争关系,底层用MCP连接工具和数据,上层用A2A做多Agent编排

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A2A和MCP在2025年底被捐赠给Linux Foundation旗下的Agentic AI Foundation共同治理

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A2A协议在2026年4月正式推至1.0版本

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MCP解决Agent连接工具的垂直问题,A2A解决Agent连接Agent的水平协作问题,两者互补而非竞争

80%

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