MCP Subagent Server

The MCP Subagent Server is a lightweight, extensible bridge that lets a high‑level “planning” agent delegate concrete work to specialized executor agents such as Claude or Amazon Q. By exposing a uniform set of tools, the server abstracts away the details of launching, monitoring, and collecting results from these external CLI agents. This removes friction for developers who want to compose complex workflows—where one agent outlines a strategy and another performs the heavy lifting—without having to write custom integration code for each tool.

At its core, the server provides four primary execution tools: , , , and . A single call to a run tool returns a unique run ID, which the parent agent can later use to poll status or stream logs in real time. The tool allows the executor to signal completion or failure and attach a concise summary, enabling the parent agent to make informed decisions about subsequent steps. These tools give developers deterministic control over external processes while keeping the MCP contract simple and consistent.

Beyond execution, the server introduces a bi‑directional messaging layer. Sub‑agents can issue messages mid‑run, and parents respond with . The parent can poll for answers using , allowing dynamic, context‑aware guidance. This feature is especially valuable in scenarios where an executor encounters ambiguous input or needs clarification on a policy constraint, enabling the overall system to adapt in real time rather than following a rigid script.

Typical use cases include automated research pipelines, where a planning agent queries Amazon Q for literature and then hands the findings to Claude for summarization; or code generation workflows, where a parent agent outlines architecture and delegates component implementation to a Claude sub‑agent. In each scenario, the server’s streaming logs give developers immediate visibility into execution progress, while status updates keep higher‑level orchestration logic informed.

The Subagent Server’s design offers several standout advantages: it supports multiple executor types with a single API, it preserves the stateful nature of long‑running tasks through run IDs, and its message passing mechanism keeps agents loosely coupled yet highly interactive. For developers building sophisticated AI assistants that require orchestration across diverse tools, this MCP server provides a clean, protocol‑centric foundation that scales from simple scripts to complex, multi‑agent systems.