MCP vs A2A: Two Protocols That Solve Different Problems

Model Context Protocol (MCP) and Agent-to-Agent (A2A) are the two open standards reshaping how AI agents integrate with the rest of the software world. They're often confused but solve different problems: MCP standardizes how a single agent talks to tools (CRMs, databases, file systems); A2A standardizes how agents from different vendors discover and delegate work to each other. Most production stacks will use both.

Written by Max Zeshut

Founder at Agentmelt · Last updated Sep 18, 2026

MCP: agent-to-tool

Model Context Protocol, introduced by Anthropic in late 2024 and now adopted by OpenAI, Google, and most major agent frameworks, defines how an AI agent discovers and invokes external tools through a server. An MCP server exposes a set of tools (with names, descriptions, and JSON schemas), resources (read-only data the agent can browse), and prompts (reusable templates). Any MCP-compatible agent can connect to any MCP-compatible server—Slack, GitHub, Postgres, Stripe, your internal admin API—without custom integration code. See the [[model-context-protocol]] glossary entry for more.

A2A: agent-to-agent

Agent-to-Agent Protocol, introduced by Google in 2025 and rapidly gaining vendor support, standardizes how AI agents from different platforms discover each other's capabilities and collaborate on tasks. With A2A, a sales agent built on platform X can delegate a research task to a specialized data agent on platform Y, with both agents negotiating scope, exchanging structured results, and tracking the request through a shared task abstraction. See [[a2a-protocol]] for more.

Why they're complementary

Think of MCP as USB for tools and A2A as IP for agents. MCP gives one agent the ability to plug into any tool; A2A gives many agents the ability to compose into larger systems. A modern enterprise stack uses both: each agent uses MCP servers to access its tools, and the agents themselves expose A2A endpoints so other systems can delegate work to them. The combination is what enables truly cross-vendor agent ecosystems, where you're not locked into one platform's stack.

Adoption status today

MCP has clear momentum and a thousand-plus reference servers in production. Most agent platforms support it natively. A2A is earlier but accelerating—Salesforce Agentforce, Google Agent Builder, and several open-source frameworks ship A2A support. If you're building today: assume MCP is required, evaluate A2A based on whether you'll integrate with agents you don't own. For internal-only agents, A2A is optional; for any agent that may need to be called by partners or external platforms, support A2A from day one.

FAQ

Frequently asked questions.

Do I need both protocols?

For tool integrations, MCP is becoming the default and you should adopt it now. For agent-to-agent collaboration, A2A is worth investing in if your roadmap includes integrating with agents built by other teams, vendors, or partners. For a self-contained agent that calls a known set of tools and is consumed only by your own apps, MCP alone is sufficient.

Are MCP and A2A competing standards?

No—they explicitly target different layers. The two protocol teams (Anthropic for MCP, Google for A2A) have stated public intent to keep them complementary, and you'll see the same servers, agents, and platforms supporting both. Don't pick one or the other; learn where each fits in your architecture.

Can I roll my own protocol instead?

You can, but the network effects of MCP make rolling your own a costly choice. Every MCP-compatible tool you skip is one less integration you can use off the shelf. The same dynamic is forming around A2A. Build proprietary protocols only when the open standards genuinely don't fit your use case—not because they require a small learning curve.

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