Building task management for AI-native teams
MCP guides, integration walkthroughs, and build-in-public engineering notes.
Managing tasks with the Model Context Protocol (MCP)
Learn how MCP gives AI agents durable task state, shared boards, and structured tools for coordinating work with a human team.
MCP task-management security: a practical checklist
Secure an AI agent's access to task boards with scoped credentials, approvals, authorization, audit logs, and a staged rollout checklist.
agent-operationsAsync human-agent handoffs that survive clean sessions
A practical task format and board workflow for handing work between AI agents and distributed teammates without relying on chat history.
agent-operationsOne task workflow for Telegram teams and AI agents
Use Telegram for fast task capture and review while AI agents work from the same shared board—without creating a second backlog.
mcp-productivityBest MCP server for task management
What makes a good task-management MCP server, how to evaluate one, and where Kangram fits — including how it compares to wiring function-calling yourself.
mcp-productivityWhat is the Model Context Protocol (MCP)?
A developer's primer on MCP — what it standardizes, how a server exposes tools, and why it matters for AI agents that need to act, not just talk.
mcp-productivityManage tasks from Claude with MCP
Connect a task-management MCP server to Claude Code, create and assign tasks, and keep one backlog shared with your Telegram team.