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# Welcome to the A2A Community

The **Agent2Agent (A2A) protocol** is generating significant buzz across the
tech world, and for good reason! This open interoperability protocol is designed
to enable **seamless collaboration between AI agents across diverse frameworks
and vendors**. By standardizing communication, A2A aims to unlock complex
workflows, enhance productivity, and foster a new era of **"Agent
Interoperability"**. Don't just take our word for it – see what the community is
saying!

## The Word on the Street: Social Highlights

The launch of A2A has sparked lively discussions and positive reactions on various social platforms. Here's a glimpse of the excitement:

- **Rapid Interest and Adoption:** The A2A [GitHub repository](https://github.com/google/a2a) has seen an **explosive surge in popularity**. This rapid interest underscores the industry's eagerness for a standardized agent communication protocol, with many companies collaborating and contributing.

- **Microsoft's interest via Semantic Kernel:** [Asha Sharma](https://www.linkedin.com/in/aboutasha/), Head of AI Platform Product at Microsoft, [announced on LinkedIn](https://www.linkedin.com/posts/aboutasha_a2a-ugcPost-7318649411704602624-0C_8) that "**Semantic Kernel now speaks A2A: a lightweight JSON-RPC protocol that lets agents swap context, not code or credentials, over plain HTTP. Drop it into your Foundry stack for instant, secure, async interoperability with any A2A-compliant agent, regardless of modality**". The post received numerous positive reactions, including "**A2A support in Semantic Kernel is a key unlock — context-level interoperability without sharing code or creds is how agent ecosystems scale securely across clouds**".

- **Matt Pocock's Diagramming Intent:** [Matt Pocock](https://x.com/mattpocockuk), a well-known developer educator, [shared on X](https://x.com/mattpocockuk/status/1910002033018421400) "**I've just been reading the Agent2Agent technical docs - Google's new protocol for agent to agent communication. You know what that means. Let's diagram them:**". This tweet, liked and reposted hundreds of times, includes some great diagrams explaining the A2A protocol.

- **Craig McLuckie's "Hot Take":** [Craig McLuckie](https://www.linkedin.com/in/craigmcluckie/) shared his initial thoughts on [LinkedIn](https://www.linkedin.com/posts/craigmcluckie_hot-take-on-agent2agent-vs-mcp-google-just-activity-7315939233792176128-4rGQ) "**Hot take on Agent2Agent vs MCP**". His post highlighted Google's careful positioning of A2A as focused on interactions _between_ agentic systems, rather than agents interacting with resources (the focus of MCP). This distinction is crucial for improving models' ability to understand expectations from other agents. McLuckie also pointed out the potential for A2A to enable systems to **advertise specific capabilities and specialities**, which is seen as "**sensible**".

## Community deep dive videos

- [Zachary Huang](https://www.youtube.com/@ZacharyLLM) explains in his [YouTube video](https://www.youtube.com/watch?v=wrCF8MoXC_I), A2A "**complements**" MCP. While MCP acts as a "**USB-C port for AI applications**" connecting agents to tools, A2A acts as a communication standard **between the intelligent agents themselves**. This layered approach allows for building powerful systems where agents use A2A to coordinate and MCP to access necessary tools.
- [Jack Herrington](https://www.youtube.com/@jherr) on his [YouTube video](https://www.youtube.com/watch?v=voaKr_JHvF4) walks through some of the provided examples and closes with his opinion that **"Having a specific protocol for agents to talk to other agents is valuable"** and reiterates, **"LLM plus tools are agents. MCP gives agents those tools. So that's why A2A and MCP play really nicely together**".
- [Cole Medin](https://www.youtube.com/@ColeMedin) suggested on his [YouTube video](https://www.youtube.com/watch?v=ywMWpmOOaSo) that "**A2A was released very recently but it's already looking like it's going to follow a similar path**" to MCP in terms of growing interest. He also demonstrates the samples step by step and provides a summary of core concepts.
- [Sam Witteveen](https://www.youtube.com/@samwitteveenai) covered A2A on his [YouTube video](https://www.youtube.com/watch?v=rAeqTaYj_aI) immediately after Google Cloud Next, discussing the value of making protocols open and not ending up with conflicting protocols.

## Community Contributions to A2A

- Python Quickstart Tutorial [PR\#202](https://github.com/google/A2A/pull/202)
- LlamaIndex submitted a sample implementation [PR\#179](https://github.com/google/A2A/pull/179)
- Autogen sample server [PR\#232](https://github.com/google/A2A/pull/232)
- AG2 \+ MCP example [PR\#230](https://github.com/google/A2A/pull/230)
- PydanticAI example [PR\#127](https://github.com/google/A2A/pull/127)
- Go example [PR\#52](https://github.com/google/A2A/pull/52)
- Daytona sandbox running agent [PR\#170](https://github.com/google/A2A/pull/170)

## What is Driving This Excitement?

The enthusiasm surrounding A2A stems from its potential to address key challenges in building sophisticated AI applications:

- **Breaking Down Silos:** A2A aims to overcome the limitations of siloed AI systems by providing a **universal framework for agents built on different platforms to communicate and collaborate securely**.

- **Enabling Complex Collaboration:** For tasks that require the expertise of multiple specialized agents, A2A provides a standardized way for them to **delegate tasks, exchange information, and coordinate actions**. This mirrors how human teams work together, distributing responsibilities for greater efficiency.

- **Dynamic Agent Discovery:** A key feature of A2A is the ability for agents to **discover the capabilities of other agents** through standardized "**Agent Cards**". This dynamic discovery allows for more flexible and adaptable multi-agent systems.

- **Complementary to MCP:** As stated on our [A2A ❤️ MCP topic page](topics/a2a-and-mcp.md) and affirmed by many community, A2A "**complements**" MCP. MCP acts as a communication standard between models and resources, providing tools for agents. A2A acts as a communication standard **between the intelligent agents themselves**. This layered approach allows for building powerful systems where agents use A2A to coordinate and MCP to access necessary tools.

- **Open and Community-Driven:** Google has released A2A as **open source**, inviting contributions from the broader community to refine and expand its functionality. This commitment to open collaboration fosters innovation and broad adoption.

## The Future is Interoperable

The social media buzz surrounding Google's A2A protocol clearly indicates a strong interest and belief in its potential to revolutionize the development of multi-agent AI systems. By providing a standardized way for AI agents to communicate and collaborate, A2A is poised to unlock new levels of automation, efficiency, and innovation. As enterprises increasingly adopt AI agents for a wide range of tasks, A2A represents a crucial step towards realizing the full power of interconnected AI ecosystems.

Stay tuned for more updates and join the growing community building the future of AI interoperability with A2A!
