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To orchestrate parallel coding agents, you coordinate them using isolated git worktrees and automatic report generation. This allows multiple agents to work concurrently on distinct project features with explicit dependencies and auto-merging upon completion.

A multi-agent mission DAG is a directed acyclic graph that maps complex software tasks with explicit dependencies. You need it when planning parallel-agent execution for building APIs or services where isolated worktrees and automatic merging are beneficial.

Setting up isolated git worktrees for parallel coding agents involves integrating MCP to auto-dispatch agents into separate worktree branches. This isolates their changes before automatically merging completed work back into the main project.

Yes, multi-agent orchestration is designed for building APIs and services with complex dependencies. It creates mission DAGs to manage parallel-agent execution in isolated worktrees, ensuring dependencies are respected during automatic dispatch and merging.

The best way to monitor parallel coding agents in isolated worktrees is by using progress dashboards. These dashboards track auto-dispatched agents and generate structured reports for stakeholders upon task completion.

Yes, MCP integration is required to coordinate multiple coding agents across isolated worktrees. The end-to-end workflow relies on MCP to handle project planning, mission creation, auto-dispatch, and progress monitoring.