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MCP Kanban Memory

@eyalzh

Repository

Basic information

Category

Memory & Knowledge

License

MIT

Transports

stdio

Author

eyalzh

About MCP Kanban Memory

MCP server providing kanban-based task management memory for complex multi-session workflows with AI agents

#mcp#project-management#kanban#memory-bank#mcp-server

MCP Kanban Memory config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "kanban-mcp": {
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "-i",
        "-v",
        "/path/to/db:/mcp",
        "mcp/mcp-kanban"
      ]
    }
  }
}

MCP Kanban Memory tools

7

Create a new kanban board to plan and keep track of your tasks.

Add a new task to the landing column (to-do) of a kanban board.

Move a task from one column to another, respecting WIP limits.

Delete a task.

Get the full info of a kanban board, including columns and tasks.

Get the full info of a task, including its content.

List all kanban boards in the database.

Overview

What is MCP Kanban Memory?

MCP Kanban Memory provides kanban-based task management state for AI-driven development. It structures an AI agent’s work by documenting and saving tasks in a kanban board, both during planning and execution sessions. It is similar to other task management MCP tools but adds column capacity limits, an embedded SQLite database, a web UI for observation, and predefined prompts.

How to use MCP Kanban Memory?

Clone the repository and run npm ci and npm run build for the shared/db and mcp-server directories. Add the server to your MCP client (e.g., Claude Desktop) using the provided JSON configuration, setting the MCP_KANBAN_DB_FOLDER_PATH environment variable to a writable folder. Use the predefined MCP prompts (create-kanban-based-project or make-progress-on-a-project) or ask the AI directly to create a board, add tasks, move them, and resume work later. A Docker installation option is also available.

Key features of MCP Kanban Memory

  • Column capacity / work-in-progress limits
  • Embedded SQLite database for persistence
  • Web UI to observe and modify tasks
  • Predefined prompts for starting and resuming workflows

Use cases of MCP Kanban Memory

  • AI-driven development planning: create a board, divide a project into tasks, and track completion.
  • Resuming a paused session: find

Comments

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