Agent-to-Agent Interoperability: How it defines the future of AI agents in the enterprise

AI agents are rapidly becoming foundational to modern enterprise operations—powering everything from routine tasks to complex, cross-functional workflows. They’re already assisting with procurement, onboarding new hires, and triaging support tickets across the enterprise.

But as organizations aim to scale their agent deployments, two roadblocks emerge:

• Lack of shared tool access – Agents operate in silos with no universal way to invoke APIs across apps.
• Lack of interoperability – Even when you have multiple agents, they can’t collaborate if they don’t speak a shared protocol.

This is the current state of agentic automation: promising, but fragmented. To move from isolated automations to cohesive, cross-functional workflows, we need agents to access more tools and collaborate across boundaries.

That’s where open protocols like MCP and A2A come in—and why Ema is investing deeply in both.

Why Agentic Business Automation Needs Interoperability

Enterprises already depend on hundreds of applications—HR in Workday, tickets in Jira, finance in Oracle, supply chain in SAP. Most AI initiatives stumble at the last‑mile integration step because every application speaks a different dialect. The challenge compounds when enterprise workflows span agents built on different platforms or frameworks—like a quoting agent running in Co‑Pilot and an auditing agent built with LangGraph. Without a common language, these agents can’t collaborate, leading to fragmented automation silos rather than cohesive transformation.

This lack of interoperability isn’t just a technical problem—it’s a strategic bottleneck. Without shared protocols:

• Agents duplicate work instead of coordinating
• Developers rebuild the same integrations across platforms
• Enterprise AI becomes brittle and unscalable

To unlock true agentic automation, we need an open mesh, or, in other words, a standardized way for agents to talk, delegate, and act across systems.

Enter A2A: A Protocol for Cross-Agent Communication

That’s why Google introduced the Agent-to-Agent (A2A) protocol. While MCP handles how models talk to tools, A2A focuses on how agents talk to each other.

In our last blog, we dove into the state of MCP in the enterprise, and how Ema elevates it to a Generative MCP to unify how agents interact with tools. Ema provides 200+ prebuilt connectors—spanning Workday, ServiceNow, SAP, Oracle HCM, and more. By embedding an MCP server inside our Agentic OS, customers can also connect any third-party tools that conform to MCP. This unlocks a dramatically expanded tool surface for every Virtual AI Employee.

But while MCP streamlines model-to-tool interactions, A2A fills the gap for agent-to-agent communication—allowing agents to discover, delegate, and collaborate across boundaries of cloud, vendor, or runtime.

Here’s what A2A brings to the table. Together, A2A and MCP unlock a powerful new model: an open mesh of agents that can reason, act, and coordinate across the enterprise.

How Ema Uses A2A + MCP to Power the Open Agentic Mesh

Ema enables customers to use any tools available through any MCP Server. We’ve also partnered with Google to adopt the new A2A protocol for cross-agent communication.

Here is how it can look like with both MCP and A2A:

This can enable different ways to integrate with agents on other platforms.

#1: A2A allows Ema to access capabilities provided by non-Ema agents

#2: A2A allows non-Ema agents to access capabilities provided by Ema virtual AI employees

Let’s look at a simplified real-world example to see how these protocols enable powerful multi-agent workflows inside Ema’s platform:

1. Discovery – When an Ema “RFP Writer” agent spins up, it publishes an A2A Agent Card and scans the customer’s agent registry. It finds a supplier-pricing agent hosted on a different platform (e.g. built using LangGraph).
2. Capability Matching – The RFP Writer sees—via A2A—that the supplier agent offers real-time pricing capabilities.
3. Task Delegation – The RFP Writer opens a shared Task Thread, sends a “Quote line-item pricing” request, and includes structured product SKUs.
4. Tool Invocation via MCP – The supplier agent, in turn, uses its local MCP server to call a NetSuite pricing micro-service, fetches the quote, and posts the result back.
5. Human-in-the-Loop (HITL) – If the workflow needs human approval (e.g., due to pricing thresholds), the supplier agent can trigger a standardised HITL experience. Thanks to A2A, it’s consistent across systems.
6. End-to-End Governance – All agent-to-agent and agent-to-tool interactions pass through Ema’s Agent Catalog & Governance Layer, which enforces security policies, logging, and RBAC.

The result? A modular, scalable, and policy-compliant workflow where agents can both act and delegate across organizational and vendor boundaries—without brittle, point-to-point glue code.

How it All Comes Together

Ema uses a two-pronged approach to enable an open agentic fabric for enterprises.

• Conversational, Horizontal Platform to Work with AI Agents: Ema's Generative Workflow Engine (GWE™) enables you to conversationally create and deploy a cross-functional mesh of AI Agents—AI Employees—through a no-code interface. This allows technical and non-technical users to easily build, deploy, and scale agentic automation, adapting to changing business needs. This robust horizontal approach allows you to solve complex business problems end-to-end with superhuman accuracy, speed and cost optimization, using EmaFusion™, with access to a wide range of enterprise tools and systems.
• Commitment to Open Standards and Interoperability: We work with industry-standard protocols to increase access to external tools and agentic capabilities, such as the Model Context Protocol (MCP) and Agent-to-Agent (A2A) protocols. This makes sure Ema’s automation is composable, extensible, and collaborative, facilitating seamless integration and future-proofing enterprise AI investments.

Ema’s investment in a horizontal, conversational, no-code experience and interoperability delivers immediate and strategic value to enterprise automation teams:

• Massive Tool Surface: Leverage 200+ native Ema connectors and instantly plug into any MCP-compliant tool built by internal teams, vendors, or partners.
• Plug-and-Play Agents: Add best-in-class agents to handle specific roles—like finance copilots, infosec scouts, or ML ops sentinels—that can instantly collaborate with existing AI Employees.
• Ecosystem extensibility, where partners and internal teams can safely publish their own agents and tools and add to their automations.
• Governable AI systems: All data flows are governed, logged, and compliant with leading standards (SOC 2 Type I & II, HIPAA, ISO 27001, and ISO 42001).

By combining MCP for universal tool access and A2A for agent collaboration, Ema delivers a horizontally scalable automation fabric where agents can independently act, delegate, and collaborate—across teams, tools, and trust boundaries.

We believe MCP and A2A are just the beginning. As new open protocols emerge—including areas like hybrid knowledge retrieval—Ema’s architecture is ready to evolve. Our commitment to open interoperability ensures that whatever comes next, your enterprise won’t just keep up. It will lead.

If you’re interested in learning more, set up a demo today.