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Connect AI assistants to Kanboard for project and task management.
This MCP tool is an open-source MIT project with no declared secrets and no declared remote endpoint in the provided materials, and no clear high-risk red flags are evident. Caution is still warranted because it runs as a local MCP server and is designed to expose or manipulate Kanboard project-management data; documentation is sparse and community adoption is low.
The materials explicitly state that no keys or environment variables are required. There is no evidence here of API tokens, account passwords, or other sensitive credentials being requested, so credential-exposure risk appears low based on the available information.
The description says it exposes Kanboard API functionality, which implies it would typically communicate with a Kanboard service, yet no remote endpoint is declared in the materials. There is no explicit evidence of data being sent to unrelated third parties, but the actual egress destination and scope are not transparent and should be verified.
The system checks indicate that this tool executes code. As an MCP server, this typically means starting a local process and handling requests. That is a normal capability for this class of tool, and the provided materials do not show requests for unusual system privileges or unrelated high-risk operations.
Its purpose is to let an LLM interact with a Kanboard project-management system, which implies possible read/write access to boards, tasks, projects, and similar business data. The materials do not indicate local file access or clearly excessive permissions beyond Kanboard-related functions, but access to Kanboard data should still be limited by least privilege.
Positive factors include that it is open source and MIT-licensed, so the code can be audited. However, it comes from a third-party registry, the GitHub repository shows 0 stars, maintenance status is unknown, and the README is absent, which limits transparency and maturity. There are no concrete red flags strong enough to make this high risk, but supply-chain trust should still be treated cautiously.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Kanboard MCP Server" yet — see the docs or source repo.
After connecting to Kanboard, read all todo tasks in the 'Product Iteration' project, group them by assignee and due date, identify overdue tasks, and suggest next actions.
A grouped task overview, an overdue task list, and an actionable summary of recommendations.
Using the following requirements list, create task cards in the Kanboard project 'Mobile Sprint 12' and add descriptions, priorities, and suggested assignees for each item: login page redesign, push notification fix, analytics validation.
Structured tasks created in Kanboard, with a summary of created items and their fields.
Read task changes from the 'Client Delivery' project in Kanboard over the last two weeks, summarize completed, in-progress, and blocked items, and generate a Chinese status update suitable for a weekly meeting.
A clear project status report ready to use in weekly meetings or team updates.
Manage a personal Kanban board, notes, and code clips using natural language.
Let AI agents manage Kanban tasks across projects with real-time collaboration.
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Enable AI agents to manage kanban boards with cost tracking and local storage.
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