Enterprise connects AI employees to partner agents
An AI agent exposes itself via A2A protocol, letting partner systems and external agents call it without any custom API work.
Expose any employee as a Google A2A agent so external AI agents can discover and collaborate with your workforce.
Your AI employees speak the Agent-to-Agent (A2A) protocol, Google's open standard for AI agent interoperability. Any A2A-compatible agent can discover your employees, understand their capabilities, and send them tasks. Your workforce becomes part of a larger ecosystem of collaborating AI agents.
A2A goes beyond simple API calls. External agents can discover what your employees are capable of, negotiate task formats, and exchange structured results. A project management agent can find your research employee, understand it accepts research briefs, send one over, and receive a structured report back. Agent-native communication, not human-shaped API wrappers.
Combined with MCP support, your employees are reachable from both major interoperability standards. MCP for tool-oriented integrations (Claude, Cursor, Windsurf), A2A for agent-oriented collaborations (autonomous agents, multi-agent workflows). Two protocols, full coverage of the AI integration landscape.
Google's Agent-to-Agent (A2A) protocol defines how AI agents from different systems discover each other, exchange capabilities, and collaborate on tasks. With A2A Protocol support, every Sistava employee can be exposed as an A2A agent, making them accessible to any external agent that speaks the A2A standard.
This is the foundation of a truly interoperable multi-agent future. An external orchestration agent, a partner company's AI system, or a third-party automation platform can discover your AI employees, understand their capabilities through the A2A agent card, and call them as participants in cross-system workflows.
The A2A protocol uses agent cards to describe what an agent can do. When you enable A2A for an AI employee, Sistava automatically generates a compliant agent card that describes the employee's skills, available actions, input/output schemas, and authentication requirements. External agents use this card to understand how to work with your employee without any manual documentation.
Capability discovery is automatic. When an external A2A agent queries your employee's endpoint, it receives a current, accurate description of capabilities based on the employee's actual configuration. If you add a skill or change a tool assignment, the agent card updates accordingly.
You control which employees are A2A-discoverable and who can discover them. Public endpoints allow any A2A client to find and call your employee. Private endpoints require a specific access token, limiting access to trusted external agents. This lets you selectively open your AI workforce to external collaboration while maintaining security boundaries.
A2A protocol is designed for scenarios where agents from different organizations need to work together. A client's AI system can delegate a task to your AI employee, receive the result, and continue its workflow, without any human-mediated integration work. This is what genuine agent interoperability looks like in practice.
For organizations building AI-native products or operating in partner ecosystems, A2A support means your AI workforce can participate directly in external workflows as a first-class service provider. Your specialized AI employees become available to a much larger potential audience of agent orchestrators without you building custom APIs for each.
An AI agent exposes itself via A2A protocol, letting partner systems and external agents call it without any custom API work.
Multiple AI employees communicate with each other and with third-party agents through A2A, forming a coordinated workforce across platforms.
The AI agent registers as an A2A endpoint, making it callable by any agent built on Google's Agent Development Kit or compatible frameworks.
AI employees publish their capabilities via A2A cards. Any compatible agent in the org can discover and delegate to them automatically.
| Before | After |
|---|---|
| AI agents from different platforms cannot communicate directly. | A2A protocol gives every AI employee a standard interoperability layer. |
| Cross-platform agent workflows require custom integration work. | Any A2A-compatible agent can call the AI employee without extra code. |
| Capabilities are locked inside one platform. | The AI agent publishes its skills to the broader agent ecosystem. |
| Building multi-vendor agent pipelines takes weeks of engineering. | A2A makes cross-system delegation a configuration, not a project. |
Agent-to-Agent (A2A) is an open protocol proposed by Google that defines how AI agents from different systems discover, communicate, and collaborate. It matters because it creates a standard way for AI agents to work together across platform boundaries, similar to how HTTP standardized web communication.
Any A2A-compliant agent client can discover and call your employees using the standard protocol. No custom integration is required. The calling agent uses the agent card endpoint to discover capabilities and the task endpoint to initiate collaboration.
MCP connects AI tools to client applications like IDEs and chat interfaces, where a human is driving the interaction. A2A connects agents to other agents for fully autonomous agent-to-agent collaboration. Both protocols are complementary and both are supported by Sistava.
Yes. A2A calls appear in the Activity Feed and Execution Inspector with a clear indicator that the request originated from an external A2A agent. You have full visibility into what external agents are asking your employees to do.
Yes, the A2A protocol lets your AI employee act as a server that other agents, built on any framework, can discover and call using the open Agent-to-Agent standard. Your employee becomes part of a broader multi-agent ecosystem.
We have agents built on three different frameworks. A2A lets them all hand off work to our Sista specialists without any custom glue code between them.