AI agents are the future and they are basically moving the world right now from performing simple tasks, such as booking something, to complicated tasks, such as reconciling invoices and much more.
However, there is still a major limitation with AI agents and that is the fact that a single AI agent cannot talk with another agent in order to improve their functionality.
If you have an amazing system that is not able to communicate with other systems, then you are simply limiting its capabilities and while there are workarounds, it’s not really a reliable or predictable solution.
Google decided to solve this issue once and for all by launching the new and open protocol called Agent2Agent Protocol (A2A).
Google basically did it with the support and contribution from a lot of major players in the industry, from names such as Atlassian, Box, Cohere, Intuit, Langchain, MongoDB, PayPal, Salesforce, SAP, ServiceNow, UKG and Workday, along with service partners like Capgemini, Deloitte, PwC, TCS etc.
So, what is Agent2Agent Protocol (A2A)? Let’s find that out in this blog and along with that, we are also going to understand why Agent2Agent Protocol (A2A) matters so much, as well as how it works and much more.
What is Google’s Agent2Agent Protocol (A2A)?
Agent2Agent Protocol (A2A) is basically an open protocol that helps with inter-agent communication between multiple agents.
It does this by setting a common language as well as a common set of rules so that different AI agents from different vendors and companies, as well as frameworks, are able to understand each other and discover each other, as well as authenticate and exchange messages with each other.
This ultimately helps these different AI agents to coordinate actions with each other and can be utilised to ultimately create a foundation for multi-agent systems that go beyond single apps or organisations.
Agent2Agent Protocol (A2A) is currently being stewarded under the Linux Foundation and this is so that the project remains open and community-driven as it grows and as more people adopt it.
We must also understand that Agent2Agent Protocol (A2A) complements Anthropic’s Model Context Protocol (MCP) and it is the perfect choice for this as it provides helpful tools as well as context to agents.
We estimate that businesses are going to see a lot of benefit due to A2A and this standardisation drive is going to make platforms much more powerful and cloud environments much more connected.
The industry overall actually believes in this process a lot, which can be seen by the number of partners associated with Agent2Agent Protocol (A2A).
The Key Technologies That Make Agent Conversations Happen
HTTPS: Security All the Way
One of the fundamental factors behind any agent-to-agent conversation is that it needs to be secure and that is exactly how A2A works because every message exchanged between agents travels through the HTTPS protocol, which ensures the utmost level of security.
The reason for this is that agents at times have to handle very sensitive information and this protocol ensures privacy so that the conversation cannot be intercepted or altered for malicious purposes.
We must also understand the fact that HTTPS is just the industry standard when it comes to production environments and that is why choosing it for A2A conversations is the natural best choice.
Server-Sent Events (SSE): Updates Simplified
Sometimes the agents need to send updates in the form of real-time progress updates or updates regarding partial results, such as streaming task outputs.
In this situation, the key technology utilised is SSE or Server-Sent Events.
Server-Sent Events (SSE) are perfect for status updates as well as streaming task results and also progress notifications and SSE is preferred over WebSockets simply because it is much simpler and lighter to implement and it ensures a one-way stream from server to clients and it is also firewall and proxy-friendly, which makes it a good choice when it comes to scaling.
JSON-RPC: Simplicity in Language
Since agents need to talk with one another and need to initiate actions with other agents, such as starting a task or sending a message or even returning a result, they need to use a language format as a common way of communication.
JSON-RPC is this format and there are several reasons why.
One of the primary reasons is simply because it is a simple language that can be utilised to write requests in JSON by humans and it is a language that is quite compatible with the agents as well.
While it is not as basic as simple colloquial language like basic prompting but it is still quite human-friendly and at the same time, it also helps keep interactions structured and predictable as well as easy to implement.
Why Agent2Agent Protocol (A2A) Matters
Interoperability
Vendor lock-in is never great for something that is new and upcoming and that is why A2A is revolutionary because it is able to bring together AI agents that utilise different APIs and different frameworks all under a single roof and also keep it open and governed by the Linux Foundation.
This means users do not have to choose between different AI Agents, so they can simply utilise all of them in combinations.
This kind of interoperability is actually great for the industry because it encourages competition between different AI agent vendors and can lead to a much healthier market and better innovation.
Security & Accountability Across Boundaries
A2A addresses something quite important when it comes to accountability and trust with AI agents because the primary purpose of these agents is to do things on behalf of humans.
But when agents start to do things that are not approved, then things can get quite bad and that is why A2A utilises cryptographically verifiable identities and auditable message exchanges, which means that every request or approval can be traced back to a probable agent identity, which is going to prevent fraud and make compliance much easier.
An Ecosystem
If you do not have agents operating with each other, then you simply cannot build an ecosystem. Agent2Agent Protocol (A2A) solve this issue by creating the perfect foundation for ecosystems to work together, enabling a network effect where each agent can be added to the ecosystem and developed further and also detected by the existing systems.
This will mean even more adoption for Agent2Agent Protocol (A2A) as more companies and organisations understand A2A’s value, which will accelerate its growth and real-world deployment much faster.
Plays Nicely with Adjacent Standards
Agent2Agent Protocol (A2A) is not working in isolation because it is already a part of a stack of emerging protocols, such as MCP, as it standardises how agents connect to data and tools.
A2A will work hand in hand with MCP in standardising how agents are going to talk to each other.
This will also work in tandem with AP2 in order to ensure how agents can transact with each other securely
We believe it is the start of something much more standardised and much more stable and reliable.
How Does Agent2Agent Protocol (A2A) Work?
Establishing Trust
The very first thing the A2A needs to do is to establish and prove identity, where every agent in the ecosystem will carry a cryptographically secure and identity that can be verified and this is similar to how we use TLS certificates on websites. This identity will be verified before proceeding.
Finding Each Other
However, in order for the connection to happen, the AI agents will need to find each other so they can talk and that is why A2A supports two kinds of connections.
Direct connections, where one agent already knows the endpoint and registry-based discovery, where agents are discoverable.
Agreeing on What’s Possible
Once the trust has been established between agents, the agents are going to exchange capability manifests, which will decide if one agent is compatible with another based on what they can perform and these manifests will also describe the required inputs and outputs, as well as any policy or guardrails related to the capability of the agents.
This step is basically there to ensure alignment between different agents so that there are no issues when they actually work together.
Talking the Same Language
Now, in order for different agents of different languages to work together, a standardised communication protocol needs to be utilised and that is exactly what happens with A2A as it utilises the A2A envelope, which is basically a standardised message format with each message containing some amount of data.
This data includes the intent of the message as well as the context and response requirements and since it is broken down into these important elements, agents from different vendors can communicate with each other with ease.
Keeping Receipts
When you are doing something as critical as making agents talk to each other, documentation is quite important and A2A handles that quite well because every message exchange with the help of A2A is assigned and logged as well as time-stamped, so that it creates a permanent trail.
Playing Well with Others
The reason why A2A works so well is because it is designed to be a complement for other interoperability tech, such as MCP (Model Context Protocol) and AP2 (Agent Payments Protocol) and all of them together form a robust stack.
We hope you now understand the potential of Agent2Agent Protocol (A2A) and how it can fundamentally reshape how we utilise AI agents and how AI agents actually communicate with each other.
If you are someone willing to implement this protocol or rather implement any kind of AI agent API into your workflow, then we are here for you.
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