Model Context Protocol:
A universal format for agents to access tools, services, and data.
MCP gives your AI agents a standard way to connect with APIs as tools. It turns tool access into something discoverable, reusable, and orchestration-ready, without custom wiring for every task.
The easiest way to make tools usable by agents
The easiest way to make
tools usable by agents
Once you define roles and capabilities, the orchestration engine autonomously routes the task to the right agent, tool, or logic.
Orchestrated
Agents coordinate tool use across systems with shared context and clear execution control.
Dynamic
MCP enables real-time access to tools based on what the agent needs, when it needs it.
Modular
You define how tools are called once. Agents across flows and domains can use that same pattern.
Tools don’t rely on the model to be used
You can trigger an MCP-defined tool from a declarative policy, a condition, or a rule. The model doesn’t have to guess. The orchestration layer decides what gets called and when.
Interruptions don’t break the system
If a user changes direction mid-task, the MCP call pauses. The orchestrator tracks where the tool was triggered and what it was doing. When context stabilizes, it resumes without losing state.
Tool inputs and context are explicitly defined
You control what each tool receives, from user-provided inputs to scoped memory. That context is declared, not inferred, so your tools stay focused and secure.
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