## Key Protocols and Infrastructure: MCP, A2A, and More

To make the Agentic Web practical, industry and community leaders have introduced **open protocols** that standardize how agents communicate with each other and with tools. Two of the most important emerging standards are **MCP (Model Context Protocol)** and **A2A (Agent-to-Agent protocol)**. These are complementary: MCP focuses on connecting agents to external tools/data, and A2A focuses on agent-to-agent messaging. Let’s look at each in turn, as well as how they work together and other related efforts (like IBM’s ACP).

* **Model Context Protocol (MCP):** Developed by Anthropic in 2024, MCP is essentially an open standard for **connecting AI agents to external resources and tools** in a uniform way. The motivation is that today, every time you want an AI to use a new tool or dataset, you have to custom-integrate it. MCP instead defines a common interface: applications (tools, databases, services) expose their capabilities through an MCP **server**, and AI agents use an MCP **client** to discover and invoke those capabilities. Each tool provides metadata (function descriptions, input/output format, etc.) that agents can query via MCP, almost like an automatic API documentation. For example, an agent can ask the MCP registry what functions are available for, say, “image generation” and get a standardized description of how to call a particular image API. Then it can invoke it through a standardized request format. In short, MCP acts like a **“USB-C for AI tools”** – a universal plug that fits any tool into an agent’s context. This dramatically reduces the friction of enabling tool-use: as long as a tool has an MCP wrapper, any MCP-enabled agent can use it securely and consistently. Anthropic has open-sourced MCP with specifications and SDKs, and even provided pre-built connectors for common systems like Slack, GitHub, Google Drive, etc., to jumpstart the ecosystem. For developers, adopting MCP might mean using their SDK to expose your educational app’s functionality (e.g. a quiz bank or student database) via MCP, so that any agent (be it Claude, GPT-4, etc.) can interface with it. If you’re building an agent, using an MCP client library will let your agent tap into a growing pool of MCP-compliant tools without custom coding each integration. MCP ensures **tools are invoked in a safe, structured manner**, with authentication and usage rules standardized across platforms.

* **Agent-to-Agent Protocol (A2A):** Launched by Google in early 2025, A2A is an open protocol for **direct agent-to-agent communication and collaboration**. Its goal is to allow agents (even from different vendors or frameworks) to talk to each other, exchange messages, and coordinate actions securely over the internet. A2A provides a few key mechanisms:

  * Each agent publishes an **Agent Card** – a JSON descriptor at a well-known URL that lists the agent’s capabilities, APIs, and communication endpoints. This is like a public profile advertising what the agent can do.
  * A discovery mechanism: given a task or need, an agent can find other agents’ Agent Cards (if they are registered or known) to identify who can help. For example, a “TutorAgent” might discover a “MathSolverAgent” via its Agent Card to help solve an equation.
  * A standardized message format (built on familiar web standards like HTTP and JSON) for sending task requests and receiving results between agents. Agents establish a secure channel (with authentication akin to OpenAPI security) so that communication is trusted.
  * Support for **long-running tasks and asynchronous interaction** – A2A isn’t limited to single query/response; it supports streaming updates, partial results, and event callbacks so agents can work on multi-step collaborations over time.

  The philosophy behind A2A is to enable a *true multi-agent ecosystem*, where an agent built by Company A can seamlessly invoke the help of an agent from Company B if needed, much like one web service calling another via an API. For developers, A2A opens the door to composing **agent services across organizations**. Imagine your educational tutoring agent could, on the fly, call an external “Language Translation agent” (because it discovered the student’s question is in Spanish and your agent doesn’t speak Spanish). If both follow A2A, this can happen dynamically and securely, rather than you having to hardcode that integration. The A2A spec is open-source (Linux Foundation is involved), with reference implementations and SDKs available. In practice, using A2A might involve deploying an endpoint for your agent (so it can receive tasks from others) and implementing logic to handle incoming agent requests. It also means configuring **authentication** (possibly decentralized IDs as the spec supports) so your agent trusts who it’s talking to. The benefit is that your agent can both **offer its own specialty** to others (maybe your agent is really good at physics problems and can accept A2A queries for that), and *outsource* subtasks to other agents rather than trying to do everything alone.

* **ACP and Other Protocols:** In addition to MCP and A2A, there are other notable efforts. IBM’s **Agent Communication Protocol (ACP)**, also introduced in 2025, has a similar aim of standardizing agent interoperability and is now a Linux Foundation project. ACP is REST-based and similarly allows agent messaging across systems. The good news is that these protocols are being designed to **work together, not compete**. In fact, the literature often mentions MCP (agent-to-tool) and A2A/ACP (agent-to-agent) as complementary layers. For a developer, it’s wise to keep an eye on all these standards. They share common principles (open, JSON/HTTP-based, secure) and your agent or service might implement multiple if needed. For example, you might use MCP to let agents use your “Algebra Solver” tool, and also give that tool an agent interface via A2A so that other agents can directly ask it questions. Major tech players are pushing for ubiquity of these protocols over perfecting one dialect, to avoid the “walled garden” scenario and ensure an open agentic web.

In summary, **MCP provides the means for agents to use tools and data sources, and A2A (and ACP) provide the means for agents to talk to each other**. A developer guide from the A2A initiative succinctly says: use MCP for tools, A2A for agents. Embracing these standards in your development means your agent-based applications will be interoperable with the broader Agentic Web. This is particularly crucial in education: you wouldn’t want an educational agent that can’t query an external library database or collaborate with a scheduling agent just because of a protocol mismatch. By following open protocols, your educational agents can plug into a richer ecosystem of capabilities (and also contribute their own).