MCP vs A2A: Tools Versus Teammates
MCP connects an agent to tools and data. A2A connects an agent to other agents. They solve different problems, and serious systems will use both.
On this page
Every few months a new agent protocol shows up and the comparison posts follow. The useful way to hold MCP and A2A in your head is one sentence: MCP is for tools, A2A is for teammates. Mix them up and you will design the wrong integration.
What each protocol standardizes
Model Context Protocol (MCP) defines how an AI application connects to external capabilities. It uses a client-server model with three roles: the host (the AI application, such as an assistant), an MCP client inside it that speaks the protocol, and MCP servers that wrap a database, a file system, a SaaS API or a search service. Before MCP, each integration needed custom glue code per model and per tool.
Agent-to-Agent (A2A), introduced by Google, lets agents communicate and collaborate: delegate a task to another agent, share intermediate results, and combine capabilities. The other side is not a function, it is an autonomous system that decides how to do the work.
The difference in one table
| MCP | A2A | |
|---|---|---|
| Connects an agent to | Tools, data, APIs | Other agents |
| The other side is | A capability with a defined interface | An autonomous party with its own reasoning |
| Typical interaction | Call, get result | Hand over a goal, receive work, maybe over time |
| Failure looks like | Bad tool output, timeouts | Misunderstood goals, partial work |
| Trust question | Is this server safe to feed into my context? | Is this agent competent and authorized for this? |
How they fit together
- Each agent uses MCP for its own context
A research agent connects through MCP servers to a document store and web search. A finance agent connects to the accounting database and a spreadsheet service. Each has the tools for its own job.
- Agents use A2A to collaborate
A planning agent receives “prepare the quarterly board update”. It delegates market research to the research agent and numbers to the finance agent over A2A, then assembles the results.
- The user sees one assistant
Behind the scenes it is tools beneath each agent and a conversation between agents above them. Neither protocol replaces the other.
If the thing on the other end would give the same answer to the same input every time and has no judgment of its own, it is a tool. If it plans, chooses its own tools and can fail in creative ways, it is an agent.
The security reality of both
Anything that flows into your model’s context is a potential injection vector. An MCP server’s tool descriptions and outputs, and an agent’s replies over A2A, are both text your model will read and may obey.
Do
Treat MCP servers and remote agents like third-party dependencies: use trusted sources, scope each connection to the minimum permissions, log calls, and require human approval for irreversible actions.
Don't
Connect every server you find because it is “just a tool”. A tool that returns attacker-controlled text can steer your agent into leaking data or taking actions you never intended.
When to reach for which
- Need your agent to read a database, call an API or search files: MCP.
- Need to hand a whole sub-goal to a specialist agent, possibly run by another team: A2A.
- Need a one-off function call inside your own code: neither, just call the function.
Takeaway
Protocol names change, the layering does not. Agents need context (tools and data) and sometimes collaborators (other agents). MCP answers the first, A2A answers the second, and keeping the distinction clear stops you from building a multi-agent system where a plain tool call would do.
Frequently asked questions
Do MCP and A2A compete with each other?
No. They sit at different layers. The Model Context Protocol standardizes how one agent reaches external tools, data sources and APIs. The Agent2Agent protocol standardizes how independent agents discover each other, delegate tasks and exchange results. A system can use MCP inside each agent and A2A between agents.
What is an MCP server?
A program that exposes a capability, such as a database, file system, or SaaS API, in the standard MCP format so any MCP-capable agent can call it without custom integration code. The host application runs an MCP client that connects to one or more such servers.
When do I need agent-to-agent communication instead of just more tools?
When the other party is autonomous: it has its own reasoning, its own tools and possibly belongs to another team or company. A tool call is deterministic input and output. Delegating to another agent means handing over a goal and getting back work that may take time and judgment.
Is it safe to connect any MCP server to my agent?
No. A server's tool descriptions and outputs enter your model's context, so a malicious or compromised server can attempt prompt injection or data exfiltration. Treat servers like third-party dependencies: pin trusted sources, scope permissions tightly and require approval for sensitive actions.
Sources & further reading
Keep reading
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