MCP vs A2A: Which Agent Protocol Should You Ship?

Q: What does an MCP tool list prove?

`tools/list` proves discovery, not successful execution. The useful proof is at least one safe `tools/call` or resource read that returns a valid response under the expected auth, session, content type, and protocol-version rules.

April 15, 2026

The Spawn MCP versus A2A protocol comparison cover

Direct answer

Use MCP when an AI application needs callable tools, readable context, or reusable prompt templates. Use A2A when one agent needs to delegate work to another agent that can manage state, ask follow-up questions, stream progress, and return artifacts.

That is the practical MCP vs A2A split. In the MCP introduction, Model Context Protocol is described as an open standard for connecting AI applications to external systems such as data sources, tools, and workflows. On the complementary side, A2A and MCP says MCP connects agents to tools and resources, while A2A enables agent-to-agent collaboration.

Before writing metadata, use this rule:

Use MCP when the service is a capability an AI client should call.
Use A2A when the service is an agent that should take responsibility for a task.
Expose both when the same system needs direct tool access for AI apps and delegated task access for other agents.

A protocol label is only a routing hint. It is not proof of liveness, ownership, safety, payment readiness, or settlement. After choosing the runtime shape, run the public service through The Spawn checker, inspect comparable live listings in Agents, and register only the protocol surfaces that actually respond.

What MCP is for

MCP exposes capabilities to AI applications through a standard interface. On MCP server concepts, the protocol names three core building blocks: tools as model-callable functions, resources as passive data sources for context, and prompts as reusable instruction templates.

Choose MCP when the remote side is best described as "do this operation" or "give the model this context." Good examples include:

search a database;
read a document or API schema;
create a ticket;
check a balance;
quote a route;
prepare a payment request;
run one bounded diagnostic call against a harmless endpoint.

In this shape, the AI host or client decides when to invoke the capability. The MCP server validates the request, executes the operation, and returns a result the client can show, store, or feed back to the model.

Remote MCP also has a transport detail that matters for verification. According to the 2025-06-18 Streamable HTTP transport, servers may assign an Mcp-Session-Id during initialization; if they do, clients are required to include that header on subsequent HTTP requests. The same page says HTTP clients should include MCP-Protocol-Version on later requests.

That does not mean every MCP server always requires a session. A verifier should initialize when the transport expects it, store Mcp-Session-Id only when the server returns it, and reuse it on subsequent requests to that endpoint.

What A2A is for

Agent2Agent (A2A) is a protocol for agent-to-agent work. In the official specification, the core objects are a client, a server or remote agent, Agent Cards, messages, tasks, parts, artifacts, streaming, and push notifications. Those concepts exist because delegated agent work often lasts longer than one function call.

Choose A2A when the remote side should own part of the work. Good examples include:

a research agent that returns a sourced report;
a support agent that handles a customer case;
a risk agent that reviews a proposed action;
a deployment agent that runs a checklist and reports status;
a procurement agent that negotiates requirements across turns.

The key object is not just an endpoint. A2A discovery starts with an Agent Card: a JSON document that can describe identity, service endpoint, capabilities such as streaming or push notifications, authentication, and skills. Discovery guidance in A2A lists more than one strategy, including well-known URI, curated registries, and direct configuration or private discovery.

For product code, /.well-known/agent-card.json can be a useful default path, but it is not the only possible discovery path. A registry or explicit configuration can also point clients to Agent Cards.

Implementations also differ by protocol binding and version. Current A2A specification material includes JSON-RPC, gRPC, and HTTP+JSON/REST bindings. The HTTP+JSON binding uses routes such as POST /message:send and POST /message:stream. Product logic should read the Agent Card, select the supported binding, and keep compatibility handling in an adapter instead of hard-coding one method spelling.

MCP vs A2A comparison

Question	MCP answer	A2A answer
Primary job	Connect AI apps to tools, resources, and prompts	Connect agents to remote agents
Caller intent	"Call this capability"	"Delegate this task"
Remote side	Tool server, context server, workflow surface	Agent or agentic system
State	Often request/response, with optional transport session state	Tasks can progress through a lifecycle
Proof to collect	Initialize if needed, list tools/resources/prompts, call one safe operation	Fetch or receive an Agent Card, send a message, inspect task/message/artifact behavior
Discovery surface	MCP endpoint plus client configuration or registry context	Agent Card through well-known URI, registry, or direct configuration
Common failure	Tool list exists but calls fail, auth is unclear, schema is too loose	Card exists but send path, task lifecycle, streaming, or artifacts do not work
First product action	Verify with The Spawn checker before promoting the endpoint	Verify with The Spawn checker before promoting the agent card

The A2A and MCP topic page gives the clean mental model: MCP covers tools and resources with structured inputs and outputs, while A2A covers agents that reason, plan, maintain state, and collaborate on broader goals. Treat A2A vs MCP as an architecture boundary rather than a winner-take-all protocol fight.

When to ship MCP, A2A, or both

Ship MCP first when your strongest value is a callable capability. If your endpoint answers "search leads," "price this swap," "read this record," or "create this issue," MCP is usually the faster public contract. Keep tool names concrete, argument schemas tight, and response shapes stable. Then use spawnr or another client path only after a live check shows the endpoint is worth installing.

Ship A2A first when your service is an agent with task ownership. If the remote side needs to ask a clarifying question, hold a taskId, stream progress, return an artifact, or coordinate several internal tools, A2A is the better external surface. Publish an Agent Card, describe skills in builder-readable terms, and verify at least one real message path before claiming the agent is ready.

Ship both when you have two audiences. A research system might expose MCP tools for direct editor use and an A2A endpoint for other agents that want delegated reports. The A2A/MCP topic page frames the protocols as complementary: an agentic app can use A2A to communicate with other agents while each agent internally uses MCP for its tools and resources.

Supporting both should not duplicate business logic. Put auth, rate limits, payment checks, execution, and result storage under small protocol adapters so the MCP and A2A surfaces do not drift.

Verification checklist

Before promoting an MCP or A2A service, verify behavior rather than metadata.

For MCP:

Confirm the endpoint speaks MCP, not plain REST behind an MCP label.
Send initialization when required by the transport.
Store Mcp-Session-Id only if the server returns it.
Include the negotiated MCP-Protocol-Version on later HTTP requests when using Streamable HTTP.
Request the tool, resource, or prompt list.
Call one safe tool or read one safe resource.
Record auth errors, timeout behavior, content type, and response shape.

For A2A:

Fetch the Agent Card from the advertised path, registry, or configured URL.
Confirm the card names a usable service endpoint, skills, capabilities, and auth requirements.
Select the supported protocol binding instead of assuming one route or method spelling.
Send a bounded test message that cannot mutate production state.
Inspect whether the response is a direct message, task, status update, or artifact.
If a task is created, follow task state until it reaches a terminal state or a documented input-required state.
Classify method-not-found, unsupported version, missing auth, and empty artifacts as compatibility or readiness failures. Those responses do not prove the broader concept is invalid.

For both:

An MCP tool list or A2A Agent Card is discovery evidence, not execution proof.
A protocol declaration is not ownership proof.
A payment field or 402 response is not settled payment proof.
Keep logs free of raw secrets, wallet addresses, pair tokens, and free-form user input.
Recheck after deploys, because HTTPS metadata and endpoint behavior can change.

Payment handling belongs in a separate check. If the service charges per call, use x402 for the payment handshake, but keep payment readiness separate from MCP or A2A readiness.

The Spawn path

The Spawn keeps registration, protocol behavior, payment behavior, and installation separate because each can fail, get stuck, or recover independently. We shipped the checker around that split: a card can parse while the MCP call fails, an Agent Card can exist while message/send is unsupported, and a payment hint can appear before a usable 402 flow. Our product path sends builders to /check before it sends them to installation.

Start with the protocol decision on this page. If you are publishing an onchain agent, use ERC-8004 vs MCP to separate registry identity from runtime execution, then use registering onchain AI agents to prepare the public record.

Once the metadata is ready, run the service through The Spawn checker. The checker is the primary product action for this page because it turns the protocol claim into an observable inspection path. It can help you see whether metadata, service entries, MCP/A2A declarations, and payment hints line up with a real endpoint.

After the card looks healthy, browse live examples in Agents. If you are installing a useful agent into a local editor workflow, follow Inspect, Dry-Run, Then Install an ERC-8004 Agent with spawnr.

FAQ

How should builders compare MCP and A2A for a real service?

Neither protocol is better in isolation. MCP is better for direct access to tools, resources, and prompts, while A2A is better for delegated agent work with task state, messages, streaming, and artifacts. The right choice depends on whether the caller needs a capability call or another agent to own part of the job.

What does Agent2Agent vs Model Context Protocol mean?

A2A expands to Agent2Agent, and MCP expands to Model Context Protocol. Searchers using "A2A vs MCP" and "Model Context Protocol vs Agent2Agent" are usually asking the same decision question: should this endpoint expose callable capabilities, delegated agent work, or both?

Can one agent support both MCP and A2A?

One agent can support both. A useful pattern is A2A outside and MCP inside: remote agents collaborate through A2A, while each agent uses MCP to reach tools and resources. The same system can also expose selected MCP tools directly to AI clients when that makes installation easier.

Does an Agent Card prove an A2A agent is live?

An Agent Card describes the agent and how to reach it, but it does not prove the send path works, that tasks finish, that artifacts are useful, or that the operator is trustworthy. Verify a real message path before promoting the listing.

What does an MCP tool list prove?

tools/list proves discovery, not successful execution. The useful proof is at least one safe tools/call or resource read that returns a valid response under the expected auth, session, content type, and protocol-version rules.

Which entries belong in a listing?

List only surfaces that work today. Use an MCP service entry for direct callable capabilities, an A2A service entry for delegated agent work, and both entries only after both endpoints have been checked. The next step is to run the checker and fix the failing surface before promoting the agent.