Kanboard MCP Server

The Kanboard MCP server is a lightweight, Go‑based bridge that lets AI assistants such as Claude Desktop or Cursor interact with a Kanboard instance through natural language. By exposing Kanboard’s JSON‑RPC API as MCP tools, developers can issue high‑level commands—create a task, list projects, update user assignments—without writing any code. This eliminates the need to manually construct API calls or maintain custom scripts, enabling AI‑driven project management workflows that feel like a conversation.

At its core, the server maps Kanboard resources to MCP tools: projects, tasks, users, columns, and more. Each tool accepts plain‑English prompts that the AI translates into API requests. For example, “Create a task called ‘Design mockup’ in project 42” is parsed into the corresponding Kanboard RPC call. The server also supports authentication via API key or username/password, ensuring secure access to private boards while remaining simple to configure through environment variables.

Key capabilities include:

• Full project lifecycle management – create, update, delete projects and tasks; move tasks across columns; assign users.
• Rich query tools – list all projects, fetch a project by ID, name, or identifier, and retrieve detailed task information.
• User and role handling – manage Kanboard users and their permissions directly from the AI interface.
• Performance and reliability – built in Go, the server delivers low latency responses even under heavy load.

Real‑world scenarios benefit from this integration in many ways. A product manager can ask the AI to “Show me all tasks overdue in the Marketing board” and instantly receive an updated list. A developer can say “Add a new issue to project X with priority high” and have the task created in seconds. Teams that rely on Kanboard for workflow visibility can now embed AI assistants into their daily tools, reducing context switching and accelerating decision making.

Integrating the server into an AI workflow is straightforward: configure the MCP client to point at the executable, set the necessary Kanboard credentials in environment variables, and restart the client. Once connected, the AI’s natural language parser automatically discovers the available tools, allowing users to compose complex queries like “Create a project called ‘Launch 2025’, add tasks for each milestone, and assign them to the respective owners.” The result is a seamless, conversational interface that turns Kanboard into an intelligent, AI‑powered work hub.