Kanban MCP Server

Overview

The MCP Kanban Task Management server bridges the gap between AI assistants and structured project workflows by providing a fully‑featured kanban board that an LLM can create, update, and query on demand. Instead of treating a task list as an unstructured collection of notes, this MCP imposes the familiar columnar layout and work‑in‑progress (WIP) constraints that developers rely on in Agile environments. By exposing tools such as create-kanban-board, add-task-to-board, and move-task over the MCP API, a Claude or other LLM can autonomously generate plans, break them into actionable items, and track progress across multiple sessions—all while keeping a persistent SQLite database that survives restarts.

What Problem Does It Solve?

Modern AI assistants excel at brainstorming and drafting, but they often lack a durable state machine for tracking incremental progress. Without a structured backlog, it is hard to resume work after an interruption or to share status with teammates. The Kanban MCP solves this by offering a single source of truth that can be queried, modified, and visualized through an integrated web UI. Developers no longer need to juggle separate task trackers or manually export notes; the AI can manage its own workflow in a way that mirrors human team practices.

Core Value for Developers

For developers building AI‑augmented pipelines, this server delivers:

• Persistent state: An embedded SQLite database guarantees that tasks survive agent restarts and can be inspected outside the LLM.
• Human‑readable interface: A lightweight web UI lets stakeholders monitor progress, adjust WIP limits, or re‑prioritize tasks without touching code.
• Seamless AI integration: Predefined prompts (e.g., start a project, resume a workflow) allow the LLM to initiate or continue a kanban session with minimal context, making conversational AI feel like a true project partner.

Key Features

• Column capacity and WIP limits: Prevents bottlenecks by enforcing maximum tasks per column.
• Task lifecycle tools: Create, move, delete, and query tasks with fine‑grained metadata.
• Board management: Create new boards tied to a project goal and retrieve full board snapshots.
• Markdown support: Task content is stored in markdown, enabling rich formatting and easy export.
• Embedded DB: SQLite keeps the solution lightweight while ensuring durability.

Real‑World Use Cases

1. AI‑Driven Sprint Planning
   A developer asks the assistant to create-kanban-board for a new feature. The LLM generates an initial backlog, populates the To‑Do column, and then moves items through In Progress, Review, and Done as code is written, tested, and merged.

2. Collaborative Problem Solving
   Multiple team members can query the board via the web UI, while the AI continues to propose solutions or refactor tasks based on new requirements.

3. Automated Reporting
   The AI can regularly pull get-board-info and generate status reports, sending them to Slack or email without manual intervention.

4. Knowledge Retention Across Sessions
   Because the board is persisted, an AI assistant can pick up where it left off after a session timeout—simply asking to resume the workflow and moving tasks forward.

Integration with AI Workflows

The MCP exposes its capabilities as tools that can be invoked through natural language prompts. A typical interaction might look like:

• “Start a new project called ImageClassifier with goal train and deploy.
  → is called automatically.”
• “Add a task: Set up data pipeline with detailed steps in markdown.”
  → populates the To‑Do column.
• “Move Set up data pipeline to In Progress.”
  → respects the WIP limit and updates the board.

Because each tool returns structured JSON, developers can chain calls or embed them in larger LLM pipelines. The web UI remains available for manual overrides, ensuring that human oversight is never lost.

Standout Advantages

• Domain‑agnostic: Works for software, research, marketing, or any project that benefits from kanban visualisation.
• Low overhead: No external database servers; SQLite keeps the footprint small while providing ACID guarantees.
• Extensibility: The tool set can be expanded with custom prompts or additional columns, making it adaptable to specific team rituals.

In essence