--- title: "A2A vs MCP: What Each Protocol Does and When" description: "A2A vs MCP explained for business readers: agent to agent versus agent to tool, a side-by-side table, how they work together and what to ask a builder." url: https://nexumautomations.com/compare/a2a-vs-mcp updated: 2026-10-31 publisher: Nexum Automations, an AI consulting firm --- > Nexum Automations is an AI consulting firm that builds what it recommends. It finds where AI pays off in a company, builds it on the tools the team already uses and stays until it is live and working. Comparison # A2A vs MCP: two protocols, two different jobs Both are open protocols for AI agents, and they do not compete. Here is what each one connects, how they fit together and when a company needs either. Last reviewed October 30, 2026 6 min read Side by side ## A2A and MCP side by side Same family of ideas, different place in the system. | | A2A | MCP | | ----------------------- | ---------------------------------------------- | --------------------------------------------- | | What it connects | One agent to another agent | One AI application to tools and data | | Who starts the exchange | A client agent asks a remote agent for work | The AI application calls a tool or reads data | | What is exchanged | Tasks, status updates and results | Tool calls, data and context | | How discovery works | Agents publish an agent card describing skills | Applications list the tools a server offers | | Typical business use | Specialist agents sharing one process | An assistant reading a CRM or file store | | When neither fits | One agent does the whole job alone | A fixed integration already covers the data | The short answer In the A2A vs MCP question, MCP connects one AI application to tools and data, while A2A lets separate agents find each other and hand off tasks. One is agent to resource, the other is agent to agent. They solve different problems, so the choice depends on the job. Key points * MCP links an agent to tools and data * A2A links one agent to another agent * They complement each other, not compete * Many projects need neither one * Pick by the job, not by popularity Our data ## What buyers see in this search The first page of Google for "a2a vs mcp", counted by type of result. | | Results | | ---------------------------------------------------- | -------------- | | Articles by companies that sell a product or service | 5 of 8 | | Social and blog-platform posts | 2 of 8 | | Forums and Q&A threads | 1 of 8 | | Titles that answer this exact search | 8 of 8 | | Google features on the page | An AI Overview | The 8 organic results on the first page of Google, United States, desktop, measured with DataForSEO on October 29, 2026\. Types only: no company or product is named. ## The short answer on A2A vs MCP MCP * Agent to tool or data * App calls a tool * Reads files and records * Open standard A2A * Agent to agent * Agent hands off a task * Shares status and results * Open standard One analyst puts it simply: if A2A is about agent-to-agent communication, MCP is about agent-to-resource integration. That split is the whole difference between A2A and MCP. One lets an agent reach things. The other lets agents reach each other. Neither is better. They sit at different points in a system. ## What MCP does 1. AI app has a question It needs something outside its own knowledge 2. It finds a tool The server lists what it offers 3. App calls the tool One standard way to ask 4. Data comes back The answer returns to the app MCP is an open protocol introduced in November 2024\. It sets one standard way for AI systems to link up with outside tools, data sources and automation platforms. In plain words, a tool is something the AI can use, like looking up a customer record or creating a calendar entry. MCP gives every tool the same plug shape. We keep the full explanation in our [Model Context Protocol](https://nexumautomations.com/glossary/model-context-protocol) entry. For how it differs from a normal interface, see [MCP vs API](https://nexumautomations.com/compare/mcp-vs-api), and for document search see [RAG vs MCP](https://nexumautomations.com/compare/rag-vs-mcp). ## What A2A does * Agent card A public note on what an agent can do * Task A unit of work passed between agents * Status Progress shared while work runs * Result The finished output sent back A2A is about communication between agents. An agent is an AI system that plans and carries out tasks on its own, and a task is a unit of work one agent asks another to do. To find a partner, an agent reads an agent card: a short public description of what another agent can do and how to reach it. This matters when work is split across specialists. IBM describes multi-agent collaboration as independent agents, each with local knowledge and decision-making capacity, acting together in a distributed system. More on this in [multi-agent systems](https://nexumautomations.com/glossary/multi-agent-systems). ## How the two work together in one process 1. Request arrives A lead agent takes it in 2. Lead hands off via A2A A specialist agent gets the task 3. Specialist uses MCP It reaches the tools and data it needs 4. Result returns via A2A The lead agent assembles the answer The two protocols complement each other across enterprise AI workflows, as one explainer puts it. Picture an intake process. A coordinating agent receives a request and passes pieces to specialist agents. Each specialist then uses MCP to reach the tools and data it needs. So A2A handles the handoffs between agents, and MCP handles each agent's access to resources. ## When a company needs neither, one or both Leans toward a protocol * Several tools behind one assistant * Agents built by different teams * Work handed between specialists * A process that will keep growing Probably not needed * One agent doing the whole job * A single fixed integration * A short, simple process * No plan to add more agents Many businesses need neither. If one agent does the whole job and its connections are already built, there is nothing for a protocol to standardize. You are likely to want MCP when an AI application must reach several tools or data sources in a uniform way. You are likely to want A2A when separate agents, possibly built by different teams, must pass work to one another. Both come up once a process spans several agents and several systems. Start from the process, then decide. * Neither: one agent, a few fixed connections * MCP only: one assistant reaching many tools * A2A only: agents that need to coordinate * Both: several agents, each using shared tools ## What to ask a builder * Which steps need an agent Start from the process * Where data is reached Which systems and which access * Who approves risk A person on consequential steps * What happens on error A clear way to step in Ask which parts of your process need an agent at all, and where one agent would be enough. A good answer starts with the work, not the protocol. Ask where the agents would reach your data, and who approves actions that carry risk. Ask how a person steps in when an agent gets something wrong. If the answer to every question is a protocol name, push back. Protocols are plumbing. If you want help scoping an agent project, see our [AI agent development](https://nexumautomations.com/services/ai-agent-development) work. FAQ ## A2A vs MCP questions * ### Are A2A and MCP competitors? No. MCP connects an agent to tools and data, while A2A connects agents to each other. They address different layers, so choosing one over the other usually misses the point. * ### Can one system use both MCP and A2A? Yes, and that is a common design. Agents pass tasks to each other through A2A, and each agent reaches its tools and data through MCP. The two protocols are described as complementary. * ### Does a business need either protocol? Often not. A single agent with direct integrations can do the job without either. A protocol becomes useful when many tools or many agents need a common way to connect. * ### Who starts the exchange in each protocol? With MCP, the AI application calls a tool or reads data. With A2A, one agent asks another agent to take a task. In both, a person can still approve risky steps. * ### Which is better, A2A or MCP? Neither wins in general. Pick by the job: tool and data access points to MCP, agent handoffs point to A2A. For the wider agent picture, read our [AI agents](https://nexumautomations.com/guides/ai-agents) guide. * ### What is an agent card in A2A? An agent card is a short public description of what an agent can do and how to reach it. Other agents read it to find the right partner for a task. --- Source: https://nexumautomations.com/compare/a2a-vs-mcp Free AI diagnosis (30-minute call): https://nexumautomations.com/#book - Services: https://nexumautomations.com/services - Guides: https://nexumautomations.com/guides