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Manage file-based tasks and orchestrate work across multi-agent teams.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "mmm-team-orchestrator" yet — see the docs or source repo.
Create a new task in the task system: prepare release notes for next week's launch, assign it to the documentation team, and mark it as high priority.
A created task record with the task content, assigned team, and priority information.
Reassign the task 'fix deployment script errors' from the development team to the DevOps team, keeping the current status notes.
A confirmation that the task was reassigned successfully, showing the new team ownership.
Mark 'organize the customer feedback list' as completed and update its completion time.
A task status update showing that the task is now completed.
When development, operations, or product teams need to hand off work across groups, they can use it to create, complete, and reassign tasks in one place, reducing manual coordination.
In multi-agent workflows, it can serve as a task hub, managing task states and team ownership in a file-based way to keep agent collaboration organized.
For teams that do not want a full project management system, it offers a lighter file-based task management approach that fits automation workflows.
It is a minimal MCP server for file-based task management and multi-agent team orchestration. It supports creating, completing, and reassigning tasks across teams.
Based on the description, it uses file-based task management. For the exact file format, directory structure, or status fields, see the source repository.
The provided material does not include installation steps, runtime requirements, or key configuration details. Please see the source repository for prerequisites.
Orchestrate role-based workflows and sync team tasks with Trello.
Coordinate CLI agents across projects with file-based task boards and tracking.
Enforce structured AI workflows with dependencies, quality gates, and validated outputs.
Orchestrate multiple AI agents in real time and monitor tasks and artifacts.
Orchestrate multiple AI agents to automate complex workflows efficiently.
Orchestrate AI agent workflows with dependencies, parallel execution, and failure policies.