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Plan user stories and Kanban backlogs together through a live browser UI for AI-human collaboration.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "Story Mapper" MCP server from askskill: Run: claude mcp add 'io-github-tomatap-storymapper' -- npx -y storymapper
Use Story Mapper to build a user story map for the order-system refactor. Split it into stages: place order, pay, ship, and after-sales, then add executable story cards for each stage.
A layered story map is generated with actionable story items for each stage, ready to move into the Kanban board.
Import this week’s tasks into Story Mapper’s Kanban, and keep them visible for both the AI assistant and team members in a real-time browser-backed shared backlog.
A shared board is returned where AI and human collaborators can view and update task status in real time.
In Story Mapper, reprioritize items in the user story map according to release urgency and update the Kanban column order to match the new plan.
Priorities on both the story map and Kanban view are aligned for a single, consistent scheduling basis.
After collecting requirements, product managers can create a story map in Story Mapper and map it to Kanban so planning discussions stay consistent with less rework.
Developers can ask AI to help break down tasks during planning, and all parties stay aligned through a shared MCP-connected board.
In remote sessions, teams can rely on the live Story Mapper view to confirm assignees and statuses on the same backlog together.
Story Mapper is an MCP tool that combines a User Story Map with Kanban, using a live browser UI so humans and AI can plan the same backlog together.
The available information shows MCP integration and UI usage are required. Specific runtime, deployment, or authentication details are not provided here; see the source repository.
A normal Kanban tool mainly manages task lists, while Story Mapper emphasizes user story map and Kanban linkage, with AI agents and humans working on one shared backlog.
Collaboratively plan tasks with AI using a local kanban and dependency graph.
Manage agent tasks across Kanban stages with comments and handoffs.
Manage Kanban boards, comments, and digests for humans and AI agents.
Create, edit, and expand mind maps on mindmap.io with AI automation.
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