A2A vs MCP: When to use Agent-to-Agent vs Model Context Protocol
While leading an Agentic AI workshop last week in New York, I showed a demo node script that uses LangGraph. I oversimplified the terms “agent” and “tool” to keep things moving but an astute student mentioned that they were not agents. They were tools. And he was right.
So what is the difference between them and between the protocols they use to communicate?
Agent vs Tool — the tl;dr
- Tool: Does something specific when invoked. It’s a capability and nothing more.
- Agent: Reasons and Acts.
Agents know why they are doing something. Tools just do it. Agents have autonomy and goals. Tools do not.
An agent may have goals like:
- Get CPU usage below 80% in the next 15 minutes.
- Deploy the latest version of the app to production.
- Generate a daily sales summary and email it to the leadership team by 6 PM.
- Resolve all failing tests in the CI pipeline before the next scheduled build.
A tool may have capabilities like:
- Query a database.
- Call an external API.
- Write to a file.
- Perform calculations.
See? Tools just do stuff. Agents figure out what stuff to do and why.
In your Agentic AI apps, you use MCP and A2A protocols, MCP to invoke tools and A2A to let agents talk to each other.
What an A2A Call Is
A2A is about letting two agents talk to one another. They’re each full reasoning entities with their own goals or roles.
- Agents collaborate, critique, delegate, or debate.
- There may be back-and-forth. There may be negotiation. It may be a conversation whereas an MCP call is one and done.
- Ideal for planning, brainstorming, decision-making, reviewing content, and so forth.
A2A: let the agents hash it out.
What an MCP Call Is
MCP is a about calling functions from your agentic system. They’re simple, rigid, predictable. You provide your agentic system with a list of tools. It decides when to call each and uses MCP to do so. Want to know more about MCP?.
- Great for anything that touches the outside world: APIs, files, databases, services, etc.
- Very explicit: “Here’s the tool. Here are the args. Go run it.”
- Ideal when your agentic system needs capabilities rather than conversation.
MCP: give the agentic system a tool.
How to Choose Between Tools and Agents
When you’re writing your code, the choice comes down to whether you need work done or ideas refined. If the agentic system needs to act, give it tools. If the agentic system needs to think with someone else, give it another agent. It really is that binary.
Quick Comparison Table
| Choose MCP If… | Choose A2A If… | |
|---|---|---|
| Result is from … | Calling functions or APIs | Two agents talking |
| ---------- | ------------------ | ---------------- |
| The power is in … | The tools you define | Agent reasoning and collaboration |
| ---------- | ------------------ | ---------------- |
| Primary purpose | Execution | Deliberation |
| ---------- | ------------------ | ---------------- |
| Examples | DB query, API call, file write, automation step | Writer + reviewer, planner + executor, expert + explainer |
| ---------- | ------------------ | ---------------- |
| Predictability | High — tool calls are explicit | Medium — often nondeterministic |
| ---------- | ---------------- | ---------------- |
| It’s like a | Toolbox | Team meeting |
Bottom line
- If you’d call a function … MCP
- If you’d call a colleague … A2A
How they work together
You don’t just pick MCP or A2A. You use both. Tool calls with MCP and agent collaboration with A2A are both needed in most agentic systems with A2A being the brain and MCP being the hands and feet.