A2A vs MCP: The Complete Guide to Agent-to-Agent and Agent-to-Tool Protocols

A2A and MCP are not rival standards solving the same problem. MCP connects an AI application or agent to tools, APIs, files and data; A2A connects an autonomous agent to another autonomous agent capable of accepting, managing and completing delegated work. The most useful production architectures often use both: A2A across agents and MCP behind each agent.[^1][^2]

The shortest mental model is:

> MCP: "Use this capability." > A2A: "Delegate this objective to another agent."

That distinction determines which protocol to choose, what gets exposed, who controls the reasoning and how long-running work is represented.

The 30-second answer

MCP's official server primitives are prompts, resources and tools. A2A's key concepts include Agent Cards, messages, tasks, task states and artifacts.[^3][^4]

What MCP actually does

The Model Context Protocol standardizes how an AI-powered host connects to external capabilities. A host such as an assistant, an IDE or a custom agent creates MCP clients, and each client communicates with one MCP server. The server exposes focused capabilities while the host retains control over permissions, context aggregation and orchestration.[^5][^6]

An MCP server can expose:

• Tools: executable operations, such as create_wordpress_draft, search_crm_contacts or issue_refund.
• Resources: contextual data, such as files, database schemas, product catalogs or a customer record.
• Prompts: reusable, parameterized interaction templates selected by the user.

The specification deliberately distinguishes who controls these primitives: prompts are user-controlled, resources are application-controlled and tools are model-controlled.[^4]

MCP example: WordPress

A WordPress MCP server could expose:

Tools
- list_posts(status, limit)
- create_draft(title, content, category)
- update_meta(post_id, title, description)
- get_product_stock(product_id)

Resources
- wordpress://editorial-guidelines
- wordpress://categories
- wordpress://products/4821

Prompts
- /prepare-seo-brief
- /translate-page

An AI host can inspect these capabilities and invoke them. WordPress itself does not become a peer agent merely because it exposes MCP tools; it remains a system providing functions and context.

MCP example: export prospecting

A single export agent could use several MCP servers:

1. A company-registry MCP server to identify manufacturers in Germany. 2. A website-crawler MCP server to inspect products and certifications. 3. A CRM MCP server to detect duplicates and create qualified leads. 4. An email MCP server to prepare drafts. 5. A WordPress MCP server to publish a localized landing page.

The export agent remains the orchestrator. It decides which tool to call, combines the results and presents the final plan.

MCP example: energy audit

An energy-renovation assistant may use MCP tools to:

• Retrieve an address and cadastral information.
• Read a DPE record.
• Query weather and irradiation data.
• Run a solar-production calculation.
• Create a CRM opportunity.
• Generate a PDF estimate.

These are capabilities, not independent colleagues. The assistant is still responsible for the objective and reasoning.

What A2A actually does

The Agent2Agent protocol standardizes collaboration between independent agents built with different frameworks, languages or vendors. An A2A server publishes an Agent Card that describes its identity, skills, endpoint, supported modalities and authentication requirements. Another agent can use that contract to decide whether and how to delegate work.[^1][^3]

A2A v1.0 became the first stable, production-ready release in March 2026. It supports multiple bindings, including JSON-RPC, gRPC and HTTP+JSON/REST, and is hosted by the Linux Foundation after its original contribution by Google.[^7][^8]

A2A's central objects

• Agent Card: the agent's machine-readable business card.
• Skill: a declared area of competence.
• Message: an exchange between agents.
• Task: a stateful unit of delegated work.
• Context: continuity across related exchanges and tasks.
• Artifact: a concrete deliverable such as a report, image, spreadsheet or structured result.

A task can move through lifecycle states and request more information before completion. Artifacts can be delivered incrementally, making A2A suitable for work that takes time or produces several deliverables.[^9][^3]

A2A example: international market entry

A CEO-facing strategy agent receives this objective:

> "Assess the Spanish market for our industrial heat pump and prepare a three-month entry plan."

It delegates through A2A to:

• A market-intelligence agent for market size, regulation and competitors.
• A regulatory agent for certifications and local obligations.
• A lead-generation agent for distributors and installers.
• A financial agent for pricing and margin scenarios.
• A localization agent for Spanish messaging.

Each remote agent can use its own models, private databases and MCP tools. The strategy agent does not need to know the internal sequence of searches and calculations; it tracks tasks and consumes their artifacts.

A2A example: travel

A travel-concierge agent delegates separate goals:

• "Find a refundable Paris–Tokyo itinerary under €2,000."
• "Find a Shinjuku hotel meeting these accessibility requirements."
• "Design an art-and-technology itinerary for five days."

The flight, hotel and itinerary agents may request missing information, work asynchronously and return candidate bookings or plans as artifacts. This is more than calling search_flights; each specialist owns a sub-goal.

A2A example: multi-company supply chain

A manufacturer's procurement agent communicates with a supplier's sales agent:

1. The buyer agent requests 10,000 units with technical constraints. 2. The supplier agent checks production capacity through internal MCP tools. 3. It asks its logistics agent for delivery scenarios through A2A. 4. The logistics agent consults carrier APIs through MCP. 5. The supplier agent returns a proposal artifact. 6. The buyer agent asks for revised payment terms.

A2A is appropriate because the agents belong to different organizations and their internal tools and reasoning should remain opaque.

The architectural difference

MCP is generally vertical: an agent reaches down into tools and data. A2A is generally horizontal: an agent delegates to a peer or specialist agent. The official A2A specification explicitly defines the protocols as complementary.[^2][^1]

                         A2A
┌──────────────────┐  objective/task  ┌──────────────────┐
│ Orchestrator     │ ───────────────► │ Specialist agent │
│ agent            │ ◄─────────────── │                  │
└────────┬─────────┘   artifact/status└────────┬─────────┘
         │ MCP                                  │ MCP
         ▼                                      ▼
┌──────────────────┐                   ┌──────────────────┐
│ CRM, WordPress,  │                   │ Private database,│
│ analytics, email │                   │ APIs, calculators│
└──────────────────┘                   └──────────────────┘

A frequent design error is to expose every low-level API as another "agent." If a component merely reads inventory or sends an email, it is usually a tool and MCP is the cleaner interface. Conversely, flattening a sophisticated specialist agent into dozens of MCP tools can leak its internal complexity and force the caller to reproduce its orchestration.

Twelve practical comparisons

1. Read a file

Request: "Read the Q3 sales spreadsheet." Use MCP. The spreadsheet is a resource; no autonomous collaborator is necessary.

2. Analyze a company

Request: "Give me the company's revenue from its latest filing." Usually MCP. A filing/database tool can retrieve the figure. Use A2A if the request becomes: "Perform full commercial due diligence, resolve contradictions and deliver an investment memo." That is a delegated goal with a deliverable.

3. Publish a WordPress draft

Request: "Create this approved article as a draft." Use MCP. create_draft is a bounded action.

4. Run an editorial desk

Request: "Monitor five competitors, select meaningful developments, commission updates and maintain our editorial calendar." Use A2A to delegate to an editorial agent. The editorial agent can use MCP to search sources, inspect WordPress and create drafts.

5. Check WooCommerce stock

Request: "How many units of product 4821 are available?" Use MCP. A get_product_stock tool is sufficient.

6. Negotiate replenishment

Request: "Prevent stockouts while keeping inventory below 45 days and negotiate the next order with suppliers." Use A2A between procurement, supplier and logistics agents; use MCP internally for ERP, inventory and carrier access.

7. Send an email

Request: "Send this approved message to Marie." Use MCP, with explicit confirmation for the side effect.

8. Conduct outbound prospecting

Request: "Build and run a compliant French-to-German distributor campaign, adjusting targeting from replies." Use A2A if prospecting is delegated to a specialist agent that manages research, segmentation, conversations and feedback. That agent may use MCP for databases, email and CRM.

9. Book one known flight

Request: "Book AF276 on 18 November after I approve the fare." Use MCP to call the booking API, with user confirmation.

10. Organize an entire business trip

Request: "Organize my Tokyo trip around these meetings, optimize cost and flexibility, and handle changes." Use A2A for a travel agent that coordinates several providers and long-running tasks. Its booking functions can be MCP tools.

11. Calculate solar production

Request: "Estimate annual production for this roof geometry." Use MCP to invoke a deterministic calculator and retrieve weather data.

12. Design an energy-renovation plan

Request: "Compare heat pump, insulation and solar scenarios, check incentives, identify installers and produce a phased investment plan." Use A2A for collaboration among audit, incentives, engineering and procurement agents; each agent can use MCP to access data and calculators.

One workflow using both

Consider an export-development system for a French industrial SME.

Step 1: delegation through A2A

The principal agent delegates three tasks:

Market agent:
"Evaluate demand, regulation and competitors in Poland."

Lead agent:
"Identify and qualify 75 Polish distributors."

Localization agent:
"Create Polish positioning and campaign assets."

Step 2: execution through MCP

The market agent uses MCP to query trade data, regulatory databases and web-search tools. The lead agent uses company registries, enrichment services and the CRM. The localization agent reads brand guidelines and writes WordPress drafts.

Step 3: A2A task updates

The lead agent reports input-required because the target annual revenue threshold was not specified. The principal agent supplies it. The task then continues rather than restarting from zero.

Step 4: artifacts

The specialists return:

• A market report.
• A scored lead spreadsheet.
• A localized messaging document.
• A campaign-import file.

The principal agent synthesizes these artifacts into an executive plan.

What the wire-level concepts look like

The following simplified objects illustrate the conceptual difference; they are educational examples rather than drop-in production payloads.

Simplified MCP tool

{
  "name": "get_product_stock",
  "description": "Return current stock for a WooCommerce product",
  "inputSchema": {
    "type": "object",
    "properties": {
      "productId": { "type": "integer" }
    },
    "required": ["productId"]
  }
}

The caller knows the specific operation and supplies its arguments. The tool returns information or performs a bounded action.

Simplified A2A Agent Card

{
  "name": "European Distributor Research Agent",
  "description": "Finds and qualifies B2B distributors in Europe",
  "version": "1.0.0",
  "url": "https://agents.example.com/a2a",
  "skills": [
    {
      "id": "qualify-distributors",
      "name": "Distributor qualification",
      "description": "Researches, scores and documents distributors",
      "inputModes": ["application/json", "text/plain"],
      "outputModes": ["application/json", "text/csv"]
    }
  ]
}

The caller discovers a specialist capable of owning a goal. It does not need to see whether that specialist uses five APIs, a human analyst, an internal model or twenty MCP calls.

State, time and autonomy

The protocols overlap technically more than the slogan "tools versus agents" suggests. MCP supports streaming, notifications, cancellation, elicitation and model sampling; A2A supports immediate messages as well as stateful tasks. The decisive distinction is therefore not whether a request is asynchronous, but where autonomy and responsibility sit.[^10][^11][^12]

Microsoft's architecture guidance reaches the same practical conclusion: use MCP for authenticated access to tools and data, and A2A for cross-platform agent integration with published contracts.[^11]

Transport differences

MCP 2026-07-28 standardizes two main bindings:

• stdio, in which the client launches a local MCP server subprocess.
• Streamable HTTP, in which each JSON-RPC message is sent by HTTP POST and the reply is JSON or a request-scoped SSE stream.[^13][^14][^15]

A2A v1.0 supports JSON-RPC, gRPC and HTTP+JSON/REST bindings over web infrastructure. That makes it naturally suited to independently deployed services and cross-platform communication.[^8][^1]

This does not mean "MCP is local and A2A is remote." MCP supports remote HTTP servers, while A2A agents may run locally. The real difference remains their interaction contract.

Security implications

Neither protocol makes an agentic architecture safe automatically. Both define communication mechanisms; implementers remain responsible for identity, authorization, least privilege, data governance, validation and auditability.

MCP risks

• Tool poisoning or misleading descriptions.
• Excessively broad tools such as unrestricted SQL or shell execution.
• Prompt injection from resources.
• Confused-deputy and token-forwarding problems.
• Destructive side effects without confirmation.
• Sensitive resources exposed under overly broad scopes.

For HTTP transport, MCP provides an authorization framework, while stdio deployments are expected to obtain credentials through the environment rather than use the HTTP authorization flow.[^16][^17]

Practical controls include:

• Separate read and write tools.
• Require explicit approval for publishing, sending, deleting, paying or refunding.
• Validate every argument server-side.
• Restrict scopes per server and user.
• Treat retrieved content as untrusted data.
• Record tool calls and outcomes without leaking secrets.

A2A risks

• Trusting a fraudulent or compromised Agent Card.
• Delegating sensitive goals to an unapproved external agent.
• Data leakage through messages, context or artifacts.
• Excessive delegation chains with unclear accountability.
• Malicious artifacts or prompt injection returned by peers.
• Ambiguous responsibility when several agents act across organizations.

A2A relies on established HTTP security patterns: production traffic uses HTTPS; authentication requirements are declared through the Agent Card; credentials are acquired out of band and sent through appropriate HTTP headers. Sensitive Agent Cards should themselves be access-controlled and should not contain plaintext secrets.[^18]

Practical controls include:

• Maintain an allowlist or trust registry for agents.
• Verify identity, ownership and advertised endpoints.
• Sign and scan artifacts.
• Limit data shared with each delegated task.
• Propagate user identity and authorization deliberately, never implicitly.
• Set delegation depth, budget and time limits.
• Maintain end-to-end task and audit correlation IDs.

Common misconceptions

"A2A replaces MCP"

False. A2A v1.0 documentation explicitly describes MCP as the agent-to-tool layer and A2A as the agent-to-agent layer.[^2]

"Every MCP server is an agent"

False. A server exposing read_file or get_stock does not necessarily possess an objective, planning loop or autonomous responsibility. It is better understood as a capability provider.

"Every microservice should become an A2A agent"

Usually false. A deterministic pricing API, database or calculator gains little from pretending to be autonomous. Expose it through a conventional API or MCP tool.

"Long-running means A2A"

Not automatically. A long database export can still be a tool operation. Use A2A when the remote party owns a goal and manages its workflow, not merely because execution takes time.

"MCP cannot connect to an agent"

It can. An agent can be wrapped as an MCP server. This is useful when one host wants controlled access to it as a tool. A2A becomes preferable when peer identity, delegated tasks, context continuity, opaque orchestration and artifacts matter.[^11]

"A2A automatically discovers every agent on the internet"

No. Agent Cards standardize how capabilities are advertised, but production discovery, trust registries, policy and agent selection remain architectural concerns.

When to use only MCP

Use MCP without A2A when:

• One agent or assistant owns the complete workflow.
• External components expose bounded tools or data.
• Tight centralized control is desirable.
• The integrations are mostly internal.
• The remote service does not need independent identity or task ownership.

Examples include:

• A coding assistant using GitHub, Sentry and filesystem servers.
• A content assistant using WordPress, analytics and image-generation tools.
• A sales assistant reading CRM data and drafting emails.
• An energy calculator reading DPE, weather and tariff data.
• A support assistant retrieving orders and issuing approved refunds.

When to use only A2A

Use A2A without MCP when each participating agent already has all the tools it needs and only cross-agent collaboration needs standardization.

Examples include:

• Two SaaS vendors exposing autonomous agents to each other.
• A buyer agent requesting proposals from supplier agents.
• A central concierge delegating to existing travel agents.
• A hospital coordination agent communicating with independent scheduling agents, subject to sector-specific compliance.

Even here, those remote agents may internally use ordinary APIs rather than MCP.

When to use both

Use both when independent agents must collaborate and each also needs standardized access to tools or data.

Examples include:

B2B export platform

• A2A: strategy, market-research, lead-generation and localization agents collaborate.
• MCP: each agent accesses registries, CRM, email, translation memory and WordPress.

E-commerce operations

• A2A: merchandising, procurement, support and logistics agents coordinate.
• MCP: WooCommerce, ERP, payment, carrier and helpdesk systems provide tools.

Renewable-energy marketplace

• A2A: audit, installer, finance and incentives agents exchange tasks.
• MCP: cadastral data, DPE, solar simulation, subsidy databases and CRM are tools/resources.

Publishing network

• A2A: editor, researcher, fact-checker and localization agents exchange briefs and artifacts.
• MCP: search, archives, analytics, DAM and WordPress expose capabilities.

Incident response

• A2A: security, infrastructure, application and communications agents own parallel workstreams.
• MCP: SIEM, logs, ticketing, cloud consoles and status pages expose controlled operations.

Decision framework

Ask these questions in order:

1. Is the other system merely exposing data or an operation? Use MCP. 2. Is it an autonomous specialist that can own a result? Consider A2A. 3. Must the caller control every tool and reasoning step? Prefer MCP. 4. Should the specialist's internal workflow remain private? Prefer A2A. 5. Does the work need task state, follow-up questions and artifacts? A2A is likely appropriate. 6. Does the specialist itself need CRM, files, APIs or databases? Add MCP behind it. 7. Are all agents inside one framework and one trust boundary? Native orchestration may be simpler than A2A. 8. Are agents crossing platforms or organizational boundaries? A2A becomes more valuable.[^11]

A useful test is to phrase the interaction:

• If the natural command is "call," "read," "write," "search," "calculate" or "update," it probably maps to MCP.
• If the natural command is "investigate," "negotiate," "plan," "monitor," "manage" or "deliver," it may deserve an A2A agent.

A pragmatic implementation path

Stage 1: stabilize tools

Start with APIs and MCP servers around systems of record. Separate read and write operations, define schemas and implement authorization and logs.

Stage 2: build one orchestrator

Let one agent use those MCP capabilities. This tests the workflow without immediately adding multi-agent complexity.

Stage 3: extract genuine specialists

Turn a component into an agent only when it has:

• A coherent domain responsibility.
• Its own planning or decision process.
• Multiple tools or data sources.
• A measurable outcome.
• A reason to remain operationally independent.

Stage 4: expose specialists through A2A

Publish clear Agent Cards, define task contracts and output artifacts, and establish authentication and trust policies.

Stage 5: govern the combined system

Implement tracing across A2A tasks and MCP calls, approvals for high-impact actions, cost limits, cancellation, retries and human escalation.

FAQ

Is A2A better than MCP?

No. They optimize different interfaces. MCP is usually better for controlled tool and data access; A2A is usually better for delegation between independent agents.

Can one agent use both?

Yes. This is the reference pattern: the agent exposes an A2A interface to peers and uses MCP servers to perform its internal work. The A2A specification explicitly describes this composition.[^1]

Do both use JSON-RPC?

MCP uses JSON-RPC messages. A2A offers a JSON-RPC binding but also standardizes gRPC and HTTP+JSON/REST bindings.[^19][^1]

Are both Linux Foundation projects?

Yes. A2A was originally developed by Google and donated to the Linux Foundation; MCP is also hosted by the Linux Foundation.[^20][^7]

Which protocol fits WordPress?

Use MCP to expose bounded WordPress capabilities such as reading posts, creating drafts or checking WooCommerce stock. Use A2A only when exposing an autonomous editorial, commerce or support agent that owns a broader outcome. For a hands-on walkthrough, see WordPress MCP Server: The Complete Setup Guide.

Which protocol fits n8n or Make?

Use MCP when an AI agent needs workflows exposed as tools. Use A2A when an independently operating workflow behaves as a specialist agent, accepts objectives, maintains task state and returns deliverables.

Does A2A require MCP?

No. An A2A agent can use conventional APIs, direct database access or no external tools. MCP is simply a standardized and reusable way to give it capabilities.

Does MCP require A2A?

No. Many useful AI applications need tools but no multi-agent collaboration.

Can MCP handle human input?

Yes. MCP elicitation allows a server to request structured information through the client, including form mode and URL mode for sensitive external interactions.[^10]

Can A2A return files?

Yes. A2A artifacts represent concrete outputs such as documents, images, spreadsheets or structured data and can be streamed incrementally.[^9][^3]

Is A2A stable?

A2A v1.0 was released in March 2026 as the first stable, production-ready version.[^8]

What is the current MCP specification?

As of October 2026, the latest stable specification is dated July 28, 2026. It introduced the largest revision since launch, and SDK adoption may still vary.[^21][^22]

Busony: building the right agent architecture

The difficult part is rarely choosing a fashionable acronym. It is defining the correct boundary between deterministic tools, proprietary data, autonomous agents and human approval.

Busony designs agentic systems for marketing, export development, lead generation, publishing, WordPress and business automation. A typical engagement can include:

• Mapping which functions should remain APIs, become MCP tools or become A2A agents.
• Building secure MCP servers for WordPress, CRM, data and internal workflows.
• Designing specialist agents with clear A2A task contracts.
• Connecting agents to Claude, ChatGPT, Gemini or private models.
• Implementing permissions, validation, audit logs and human approval.
• Building multilingual export and content pipelines without locking the architecture to one model vendor.

The objective is not to maximize the number of agents. It is to create the smallest reliable system that can delegate complex work while keeping data, permissions and business decisions under control.

Contact Busony to design the right mix of MCP tools and A2A agents for your organization.

References

[^1]: Agent2Agent (A2A) Protocol Specification — A2A Project. [^2]: Agent2Agent (A2A) Protocol — A2A Project. [^3]: Key Concepts — Agent2Agent (A2A) Protocol. [^4]: Server overview — Model Context Protocol. [^5]: Architecture — Model Context Protocol. [^6]: Understanding MCP clients — Model Context Protocol. [^7]: Agent2Agent (A2A) Project — GitHub. [^8]: A2A Protocol Ships v1.0: Production-Ready Standard for Agent-to-Agent Communication — A2A Project. [^9]: Key Concepts — Agent2Agent Protocol (A2A). [^10]: Elicitation — Model Context Protocol. [^11]: Multi-agent patterns — Microsoft Learn. [^12]: Cancellation — Model Context Protocol. [^13]: Transports overview — Model Context Protocol. [^14]: Streamable HTTP — Model Context Protocol. [^15]: stdio — Model Context Protocol. [^16]: Basic overview — Model Context Protocol. [^17]: Authorization — Model Context Protocol. [^18]: Agent2Agent (A2A) Protocol Specification — A2A Project. [^19]: Specification — Model Context Protocol. [^20]: Model Context Protocol — GitHub. [^21]: Release notes — Model Context Protocol blog. [^22]: Releases — modelcontextprotocol/modelcontextprotocol, GitHub.