The Internet of Agents: MCP, A2A, and What Comes Next

2025 witnessed the early formation and consolidation of open protocols for agentic AI. 2026 is when those protocols started to matter in production. We're watching the outlines of an "internet of agents" emerge — a world where autonomous agents discover one another, communicate, invoke tools, transact value, and coordinate work across organizational and platform boundaries.

The Protocol Stack

The current agentic protocol stack has three layers:

Tool Calling: MCP (Model Context Protocol)

MCP, developed by Anthropic and now widely adopted, defines how agents invoke external tools and data sources. It's the HTTP of the agentic web — a simple, standardized way for agents to call capabilities they don't own.

// MCP server definition — any agent can now call your tools
import { MCPServer } from "@anthropic/mcp"

const server = new MCPServer({
  tools: {
    search_codebase: {
      description: "Search the codebase for patterns or symbols",
      parameters: z.object({
        query: z.string(),
        path: z.string().optional()
      }),
      handler: async ({ query, path }) => {
        return await ripgrep.search(query, path)
      }
    }
  }
})

server.listen(3001)

Once you expose a tool via MCP, it's callable by any MCP-compatible agent — Cursor, Claude Code, or your own custom agent. You write the tool once; any agent benefits.

Agent-to-Agent: A2A Protocol

While MCP handles tool invocation, A2A handles agent coordination. Two agents that speak A2A can delegate subtasks to each other, exchange context, and compose their capabilities.

A practical example: your customer support agent receives a billing question. Instead of trying to answer it directly, it delegates to your billing agent via A2A, receives a structured response, and synthesizes the final answer for the customer. Neither agent needs to know the other's internals.

// A2A delegation
const supportAgent = new A2AAgent({
  capabilities: ["handle_support_request"],
  peers: {
    billing: "https://agents.yourcompany.com/billing",
    technical: "https://agents.yourcompany.com/technical"
  }
})

const response = await supportAgent.delegate({
  to: "billing",
  task: "explain_invoice",
  context: { customer_id: "cus_123", invoice_id: "inv_456" }
})

Commerce: ACP and x402

The most experimental layer — but the one with the most interesting implications — is agentic commerce. ACP (Agentic Commerce Protocol) and x402 define how agents transact value autonomously.

An agent that needs to search a premium database can pay for that query micropayment-by-micropayment, without any human authorizing each transaction. Budget limits and spending policies are encoded at the agent level.

What This Changes for Developers

Your API is Now an Agent Interface

If you're building a public API in 2026, you need to think about how agents will consume it, not just humans. This means:

• Semantic descriptions for every endpoint (not just parameter types)
• Structured outputs that agents can reliably parse
• Idempotent operations that agents can safely retry
• Budget/rate-limit signals so agents know when to back off

Multi-Agent Architecture as Default

For any non-trivial workflow, the right architecture is now a network of specialized agents rather than a single general-purpose one:

This mirrors the move from monoliths to microservices — and comes with the same benefits (specialization, independent scaling, fault isolation) and challenges (distributed system complexity, network latency, debugging difficulty).

The Open Questions

We're still in early days. The key unsolved problems:

1. Discovery: How does an agent find another agent with the right capability? There's no DNS for agents yet.
2. Trust: When agent A delegates to agent B, how does A verify B won't do something unsafe?
3. Debugging: Tracing a failure across five agents calling each other is significantly harder than debugging a single monolith.
4. Cost attribution: In a multi-agent system, which agent is responsible for which LLM cost?

The teams solving these problems — with open protocols rather than proprietary platforms — are building the foundational infrastructure of the next decade of software. It's genuinely the most interesting systems-level work happening right now.