MCP is how one agent reaches its tools and data. A2A is how separate agents discover and talk to each other. They sit on different axes, so they stack instead of compete: an agent can speak A2A to delegate work outward and use MCP internally to do that work. If you remember one line, remember that one.
Both arrived inside roughly a year, both carry three-letter acronyms, both promise agent interoperability, and both now live under the Linux Foundation. AI assistants routinely conflate them because the marketing language overlaps. The actual specifications do not. Most explainers stop at 'they are different' and never name the one thing that resolves the confusion: the two protocols sit on different axes, so you usually want both. This page gives the plain definitions, a single worked example, a side-by-side table, and a cheat sheet you can paste into a doc.
The one-line cheat sheet
- MCP (Model Context Protocol): agent to tool. One agent connects to APIs, files, databases, and other capabilities through a standard client-server interface.
- A2A (Agent2Agent): agent to agent. One agent discovers another, sends it a task, and gets a result back across vendor and framework boundaries.
- Mental model: MCP is the agent's hands reaching for tools. A2A is two agents on a phone call dividing the work.
- They stack: A2A on the outside for delegation, MCP on the inside for execution. Choosing 'A2A or MCP' is usually the wrong question.
What MCP actually is
MCP standardizes the connection between a single AI agent and the tools or data it needs. Anthropic introduced it in November 2024, and it has become the de facto standard for agent-to-tool connectivity. The design is a client-server model: the agent runs an MCP client, each tool or data source exposes an MCP server, and the two speak a common protocol over local transports like stdio or remote transports over HTTP. A weather API, a Postgres database, a file system, and a Slack workspace can each be an MCP server, and any MCP-aware agent can call all of them without bespoke glue code.
MCP dominates the conversation on adoption. By March 2026 the protocol reached roughly 97 million monthly SDK downloads across its Python and TypeScript clients, up from a couple of million at launch. Published servers number in the thousands: the official MCP registry listed close to ten thousand server records, and Anthropic cites more than ten thousand active public servers, with still more across the broader ecosystem once community and private servers are counted. Treat the larger figures as ecosystem estimates rather than a single authoritative tally, since registries and private deployments move quickly.
What a server exposes is worth picturing concretely, because it explains why MCP is a tool interface and nothing more. A server advertises tools the agent can call, resources the agent can read, and prompts the agent can reuse. The agent never learns how the server is implemented; it learns only the shape of what it can ask for. That narrow contract is the whole point. It lets one agent reach hundreds of capabilities through a single protocol, and it keeps each capability swappable without rewriting the agent. Crucially, an MCP server is not itself an agent. It does not reason, plan, or call other agents. It waits to be called and returns a result, which is exactly the line that separates MCP from A2A.
What A2A actually is
A2A standardizes how independent agents discover each other, communicate, and hand off tasks. Google announced it on April 9, 2025, at Google Cloud Next with more than 50 launch partners, then donated it to the Linux Foundation on June 23, 2025, where it became the Agent2Agent Protocol Project with founding members including AWS, Cisco, Google, Microsoft, Salesforce, SAP, and ServiceNow. A2A targets interoperability between agents that were built by different teams, on different frameworks, possibly running in different clouds.
Each A2A agent publishes an Agent Card, a machine-readable description of its skills, input and output modalities, endpoint, and authentication requirements. A client agent reads that card to decide whether to delegate. It then sends a task that moves through a stateful lifecycle (submitted, working, completed, plus states like input-required, failed, and canceled), with streaming updates and webhook notifications for long-running jobs. That is a coordination protocol between peers, not a tool-call interface.
The Agent Card is the part that has no MCP equivalent, and it is the clearest signal that A2A solves a different problem. An MCP server says 'here are the tools you may call.' An Agent Card says 'here is who I am, what I can take on, how to reach me, and how to prove you are allowed to.' One describes a capability to be invoked; the other describes a peer to be negotiated with. The stateful task lifecycle reinforces the same point. A tool call is request and response in a single turn, while an A2A task can run for minutes, ask the caller for more input mid-flight, stream partial progress, and finish much later. You do not need that machinery to read a database row. You need it to delegate real work to an agent you do not control.
Supporting organizations grew from more than 50 at launch to over 150 within the first year, and the SDK ecosystem expanded from a single Python implementation to five languages.
Why MCP vs A2A is the wrong question
Stop framing this as a fight. MCP and A2A were never competing for the same job. The two protocols answer different questions: MCP answers 'how does this agent use a capability?' and A2A answers 'how does this agent ask another agent to do something?' Because those are orthogonal, the common production pattern uses both at once, in a layered shape worth naming plainly. A2A sits at the outer, coordination layer, where an orchestrator agent delegates tasks to peer agents. MCP sits at the inner, execution layer, where each agent reaches its own tools to actually carry out the work it was handed. Think of it as an outer loop of agents talking and an inner loop of each agent acting. Neither layer replaces the other, and a system built on one usually wants the other as soon as it grows past a single agent.
This is also why the choice rarely arrives as 'A2A or MCP.' It arrives as 'which layer am I working on right now?' If you are wiring an agent to a database, you are on the inner layer, so the answer is MCP. If you are wiring two agents together, you are on the outer layer, so the answer is A2A. A growing multi-agent system touches both layers, often in the same feature, which is why mature teams stop treating the two as alternatives and start treating them as a stack.
A worked example: one task, both protocols
Picture a trip-planning orchestrator agent that takes the request 'book me a two-night work trip to Berlin next month.' The orchestrator does not do everything itself. It delegates the flight portion to a separate, vendor-built travel agent it has never been hard-wired to. Here is where each protocol enters.
Step 1: discovery and delegation (A2A)
- The orchestrator reads the travel agent's Agent Card and sees it advertises a 'flight-search-and-book' skill with a defined input and output schema.
- It opens an A2A task: 'Find a return flight to Berlin, two nights, depart after 6pm, budget under 400 euros.'
- The task moves to working. The travel agent streams progress, then returns a completed result with three options. Nothing about the orchestrator's internal tools crossed this boundary, only the structured task and its result.
Step 2: doing the work (MCP)
- Inside the travel agent, MCP does the heavy lifting. It calls an airline-search API exposed as an MCP server, queries a fares database through another MCP server, and writes the held booking to a reservations tool through a third.
- The orchestrator, meanwhile, uses its own MCP servers to check the user's calendar and a hotel API for the two nights.
- Each agent's tool calls stay private to that agent. A2A carried the request between them; MCP executed the work within each.
Two rules tell you which protocol you need at any line of the diagram. Every arrow between two agents is A2A. Every arrow from an agent down to an API, file, or database is MCP.
MCP vs A2A at a glance
| Dimension | MCP | A2A |
|---|---|---|
| Connects | One agent to its tools and data | One agent to another agent |
| Core verb | Use a tool / read a resource | Delegate a task to a peer |
| Discovery unit | Server exposing tools and resources | Agent Card describing skills and endpoint |
| Origin | Anthropic, November 2024 | Google, April 2025 |
| Governance | Agentic AI Foundation (Linux Foundation), Dec 2025 | Agent2Agent Protocol Project (Linux Foundation), June 2025 |
| Layer in a system | Lower layer: execution | Upper layer: coordination |
Where governance actually stands in 2026
Both protocols now sit under the Linux Foundation, but in different homes. A2A became its own Agent2Agent Protocol Project in June 2025. Separately, on December 9, 2025, the Linux Foundation launched the Agentic AI Foundation (AAIF), whose founding project contributions were MCP, Block's goose agent framework, and OpenAI's AGENTS.md. MCP lives inside the AAIF. A2A is governed by the Linux Foundation but was not one of the AAIF's three founding projects, so describing the AAIF as the shared home for 'both MCP and A2A' overstates it.
The AAIF's platinum members include Amazon Web Services, Anthropic, Block, Bloomberg, Cloudflare, Google, Microsoft, and OpenAI. The signal that matters for a practitioner: the major labs and clouds are funding neutral governance for agent standards rather than fighting a format war, which lowers the long-term risk of building on either protocol.
How to decide which one you need
- Building a single agent that needs APIs, files, or databases? You need MCP. A2A adds nothing yet.
- Building two or more independent agents that must hand work to each other, especially across teams or vendors? You need A2A on the boundary between them.
- Building a multi-agent system from scratch? Plan on both: A2A for delegation, MCP inside each agent for execution.
- Integrating with someone else's agent you do not control? A2A is the contract. Its Agent Card tells you what that agent can do without you reading its code.
If a vendor pitches A2A as a replacement for MCP or the reverse, that is a red flag. A team that understands these protocols describes them as layers, because the specifications themselves were designed to be complementary.
Where MemX fits
Protocols like these decide how agents reach data; the harder question for most people is which data. MemX is a consumer AI memory app, an external memory layer over your own documents, photos, notes, and chats across Android, iOS, and WhatsApp. Instead of re-explaining your context to every assistant, you keep one personal memory that the right tools can draw on. MemX is private by architecture: per-user keys, encryption at rest, and an on-device first pass, so your memory stays scoped to you. As agent ecosystems standardize on MCP and A2A, the durable value is owning a clean, portable layer of your own context rather than scattering it across apps.
Frequently asked questions
01Is A2A a replacement for MCP?
No. MCP connects one agent to its tools and data; A2A connects separate agents so they can delegate tasks to each other. They operate on different axes and are designed to stack, with A2A on the outside and MCP on the inside. Most multi-agent systems use both.
02What is the difference between MCP and A2A?
In one sentence: MCP is how an agent uses a tool; A2A is how one agent asks another agent to do something. Hands reaching for tools versus two agents on a call dividing the work.
03Who created MCP and A2A?
Anthropic created MCP and introduced it in November 2024. Google created A2A and announced it in April 2025, then donated it to the Linux Foundation in June 2025. Both now sit under Linux Foundation governance.
04Can you use MCP and A2A together?
Yes, and that is the recommended pattern for multi-agent systems. An orchestrator uses A2A to delegate a subtask to a remote agent, and each agent uses MCP internally to call its own APIs, databases, and files. A2A carries the task; MCP does the work.
05Are MCP and A2A both governed by the Agentic AI Foundation?
Not exactly. MCP is a founding project of the Agentic AI Foundation, launched December 2025 under the Linux Foundation. A2A is governed by the Linux Foundation as its own Agent2Agent Protocol Project from June 2025, not as one of the AAIF's three founding projects.
