Agent to Agent (A2A)
The AI OS speaks A2A — the open Agent2Agent protocol — so your agents can discover and collaborate with other agents, internal or external, across frameworks and vendors. Every interaction runs under scoped identity, policy, and audit, inside your perimeter, so interoperability never costs you governance or sovereignty.
Open Interoperability
A2A is an open, vendor-neutral standard — now under the Linux Foundation — so agents from different frameworks and vendors can discover each other and collaborate.
Complements MCP
MCP connects an agent to tools and data; A2A connects agents to other agents — together they let agents act on systems and work with one another.
Governed & Sovereign
Every agent-to-agent exchange runs under scoped identity, policy-as-code, and audit, inside your perimeter — interoperability without losing control.
Agent2Agent (A2A) is an open standard for agent-to-agent interoperability — originally introduced by Google and now under the Linux Foundation — that lets AI agents from different frameworks and vendors discover each other and collaborate on tasks securely. A2A complements the Model Context Protocol: where MCP connects an agent to tools and data, A2A connects agents to other agents. The AI OS speaks A2A so your agents can interoperate with others under governance — scoped identity, policy-as-code, and audit — and sovereign deployment.
Real work spans more than one agent. As organisations build agents on different frameworks — and start to collaborate with agents run by partners and vendors — they need a common way for those agents to find each other and work together. The Agent2Agent protocol is that common standard: an open, vendor-neutral way for agents to advertise their capabilities, exchange tasks, and coordinate, regardless of who built them. Scrydon makes A2A governed: your agents interoperate over the open protocol, but every exchange runs under a scoped identity, is authorised by policy, and is captured in the audit trail — inside your perimeter — so collaboration stays accountable and sovereign.
Agent2Agent (A2A) in the Scrydon platform
One integrated, sovereign architecture. Here is where Agent2Agent (A2A) sits — highlighted against the full stack it works with.
The AI OS for Humans & AI Agents to enable your processes
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Link your processes, knowledge & data to ontologies.
Unified storage, structured compute, and secure multi-modal data processing.
Autonomous operatives with specialised skills executing tasks across systems.
Sovereign pipelines, federated APIs, and seamless connector meshes.
Secure domain federation, trusted data sharing, and cross-boundary intelligence.
Agents that discover and collaborate with each other
A2A gives agents a common language for working together. An agent advertises what it can do, other agents discover those capabilities, and they exchange and coordinate tasks over the open protocol — even when they were built on different frameworks or run by different vendors. The AI OS speaks A2A natively, then wraps every exchange in the platform's governance, so collaboration between agents is as accountable as any other action on the platform.
Capability discovery — Agents advertise what they can do, so other agents can discover and call them over the open standard.
Task collaboration — Agents delegate, exchange, and coordinate tasks with one another, rather than working in isolation.
Framework- and vendor-neutral — A2A is open, so agents built on different frameworks or run by different vendors can interoperate.
Governed every exchange — Each agent-to-agent interaction runs under scoped identity, policy-as-code, DLP, and audit, inside your perimeter.
Tools and teammates: MCP and A2A side by side
A2A and the Model Context Protocol solve complementary problems. MCP connects a single agent to the tools, systems, and data it needs to act; A2A connects agents to other agents so they can collaborate on tasks bigger than any one of them. On the AI OS, agents use both: they reach systems through MCP and work with other agents through A2A — all inside the same governed, sovereign perimeter.
MCP reaches tools and data — An agent calls tools, systems, and data through MCP — its connection to the world it acts on.
A2A reaches other agents — An agent discovers and collaborates with other agents through A2A — its connection to its peers.
Better together — Agents combine both: act on systems via MCP and coordinate with teammates via A2A, in one workflow.
One governance model — Whether calling a tool or another agent, every interaction runs under the same scoped identity, policy, and audit.
Interoperability without losing control
An open protocol that lets agents call each other is powerful — and, ungoverned, a new way for actions to cross trust boundaries unchecked. The AI OS keeps A2A accountable: every agent acts under its own scoped, least-privilege identity, each interaction is authorised by policy-as-code, data passing between agents is screened by DLP, and every exchange is captured in an immutable audit trail. Whether your agents collaborate with internal teammates or external partner agents, they do so inside your perimeter and under your control.
Scoped identity per agent — Each agent acts under its own least-privilege identity, so it can only do what it is explicitly authorised to.
Policy-as-code authorisation — A single policy decision point authorises each agent-to-agent interaction, fail-closed by default.
DLP and audit — Data passing between agents is screened, and every exchange is logged immutably with full actor context.
Internal or external, sovereign — Collaborate with agents you run or agents partners run — inside your perimeter, from air-gapped to cloud.
Frequently asked questions
What is A2A, the Agent2Agent protocol?+
How is A2A different from MCP?+
Is A2A governed and sovereign on the AI OS?+
Can my agents collaborate with external agents over A2A?+
Who created A2A and who maintains it?+
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