
A2A Protocol
Open standard for letting AI agents from different frameworks talk to each other.
In short
A2A is an open, Apache 2.0 protocol for AI agents to communicate across different frameworks. It standardizes agent-to-agent interaction without exposing internal tools or prompts.
Pick A2A Protocol if you are building multi-agent systems that need to interoperate across frameworks, teams, or vendors without leaking internals.
Skip it if you just need a single agent or are looking for a ready-made hosted agent platform rather than a wire protocol to implement.
A2A (Agent2Agent) is an open protocol specification for inter-agent communication, originally developed by Google and donated to the Linux Foundation. It defines how opaque agentic applications, built on LangGraph, CrewAI, custom stacks or proprietary platforms, can delegate tasks, exchange context, and collaborate without exposing their internal memory, tools, or prompts. It sits next to MCP in the stack: where MCP standardises agent-to-tool calls, A2A standardises agent-to-agent calls.
This is infrastructure for developers, not a SaaS. It is most relevant if you are shipping multi-agent systems that need to talk across organisational or framework boundaries, or if you are a platform vendor who wants your agents to be addressable by others. Official SDKs ship in Python, JavaScript, Java, C#/.NET, Go and Rust, and the protocol is Apache 2.0. Governance is run by a Technical Steering Committee with AWS, Cisco, Google, IBM Research, Microsoft, Salesforce, SAP and ServiceNow at the table, which gives it a credible shot at sticking as a default.
There is no pricing because there is no hosted service. The cost is engineering time to implement the spec or integrate one of the SDKs, plus whatever runtime you point it at. Expect the spec, extensions, and SDK surface to keep moving while the standard matures.
A2A is the agent-to-agent counterpart to MCP, and with the Linux Foundation plus most of the hyperscalers behind it, it has a real chance of becoming the default. Treat it as plumbing: valuable if you are shipping agent platforms or multi-vendor agent stacks, overkill if you just need one LangChain bot.
— The AI Tool Bible editorial team
Pros
- ✅ Backed by Linux Foundation with AWS, Google, Microsoft, IBM and others on the TSC
- ✅ Official SDKs in Python, JS, Java, .NET, Go and Rust
- ✅ Cleanly complements MCP rather than competing with it
- ✅ Apache 2.0, no vendor lock-in or hosted dependency
Cons
- ⚠️ A spec, not a product - you still have to build the agents
- ⚠️ Standard is young and surface area is still evolving
- ⚠️ Requires both ends to implement A2A to get value
- ⚠️ Adoption outside founding vendors is still early
Use cases
Frequently asked
- How much does A2A Protocol cost?
- A2A Protocol is free and open source under the Apache 2.0 license. There is no hosted service or subscription fee. Your costs are limited to the engineering time required to implement the specification or integrate the provided SDKs.
- What is the difference between A2A and MCP?
- MCP standardizes agent-to-tool calls, while A2A standardizes agent-to-agent calls. A2A allows opaque agentic applications to delegate tasks and exchange context across different frameworks without exposing their internal memory, tools, or prompts to other agents.
- Which programming languages are supported?
- Official SDKs are available for Python, JavaScript, Java, C#/.NET, Go, and Rust. These SDKs help developers implement the protocol specification within their existing tech stacks, whether using LangGraph, CrewAI, or custom proprietary platforms.
- Who governs the A2A Protocol?
- Originally developed by Google, A2A was donated to the Linux Foundation. It is governed by a Technical Steering Committee that includes AWS, Cisco, Google, IBM Research, Microsoft, Salesforce, SAP, and ServiceNow, ensuring broad industry support.
- Is A2A suitable for single-agent applications?
- No, you should skip A2A if you only need a single agent or a ready-made hosted platform. It is specifically designed for multi-agent systems that require interoperability across different frameworks, teams, or vendors.
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