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AI agent router
AI agent router for agorch.io orchestration
AI agent router is the control layer that directs a user’s request to the most relevant specialist agent. In agorch.io, the AI agent router is the home orchestrator that recommends specialists, manages context handoff, and helps teams move from one task to the next inside a single workspace.
Updated 2026-07-18
The problem
What teams struggle with
As AI teams add more specialists, users often face a routing problem: they know a task needs an agent, but not which one, when to switch, or how to preserve context between steps. That creates fragmented workflows, repeated explanations, and manual coordination overhead. In many setups, tools are discovered in one place, chat happens in another, and execution lives somewhere else, so the person using the system has to become the integrator. For operations, research, and support workflows, that friction slows work and makes it harder to trust which agent should handle a request. A practical AI agent router needs to reduce that uncertainty while keeping the handoff understandable and traceable.
The solution
How agorch.io helps
agorch.io solves this with an AI agent router built into an orchestration workspace and control plane. Users start in a home chat, where the orchestrator recommends specialist agents from the agent catalog based on the request. Those specialists connect over MCP via HTTP, with optional bearer token support, so the system can discover tools and run them from a consistent interface. When a task moves between agents, agorch.io supports context handoff so the conversation does not restart from zero. Guests can try the home chat on the marketing page, while the full workspace is available with an account.
How it works
Start in home chat
A guest or user begins by describing the task to the home orchestrator on the marketing page or inside the workspace.
Route to a specialist
The orchestrator recommends a specialist agent from the catalog, helping the user choose the right agent for the job.
Hand off and execute
The selected agent receives context, discovers connected MCP tools over HTTP, and runs the task in the workspace UI.
Benefits
Reduces guesswork by recommending the right specialist agent from a central orchestrator
Preserves task context during handoff so users do not repeat the same instructions
Keeps agent discovery and tool execution in one workspace instead of scattered interfaces
Supports MCP connections over HTTP with optional bearer token for specialist integrations
Lets guests preview the home chat before creating an account for the full workspace
FAQ
Expand any question for a citable answer about this topic.
It is the home orchestrator that receives a user request and recommends a specialist agent from the catalog. The goal is to make routing feel conversational instead of forcing users to manually choose every agent.