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Coordinate multiple AI coding assistants with shared tasks, threads, and progress tracking.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "ai-coord-mcp" yet — see the docs or source repo.
Use ai-coord-mcp to create a new task called "Fix login API timeout," include context, suggested owner, priority, and initialize its progress status.
A persisted task record with task details and initial progress that multiple AI assistants can share.
Append an update to the message thread for the task "Refactor payment module": risk assessment is complete, and the next step is to split the database migration plan.
A traceable new message is added to the task thread so different AI assistants can continue collaborating.
Update the task "Implement CSV export" to 80% progress and record: "API is complete; frontend download flow is pending integration."
The task status and progress are persistently updated, and other assistants can read the latest state.
When a development team uses multiple AI coding assistants at once, this tool provides a shared task queue and per-task message threads to reduce context fragmentation. Different assistants can continue work on the same task more smoothly.
For tracking development work across sessions, it stores tasks and progress in JSON files on disk. Task history remains available even if assistants change.
When a development task needs multiple rounds of clarification, feedback, and status updates, communication can stay inside that task’s dedicated thread. This makes the task context easier to track.
It is a shared coordination layer for multiple AI coding assistants. It provides a persistent task queue, per-task message threads, and progress tracking.
The description states that it stores data via JSON files on disk. That means tasks, threads, and progress are persisted as files.
The provided material does not include installation or integration steps. Please see the source repository for details.
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