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.
Public Kanban Boards — Share Your Project Status by Link
A public kanban board lets you share project status, roadmaps, and OSS task lists by link — read-only, members-only data hidden. Here is the pattern and how it compares.
Designing AI-Agent Onboarding That Actually Converts
AI-agent activation is different from SaaS activation. Here is the 7-event funnel we instrumented, the onboarding choices that move each step, and the fire-and-forget pattern behind it.
Cross-Board Task Management — Designing My Work for Multi-Project Teams
Per-board views fail the moment you have three projects. We built a single My Work inbox with attention rules across every board. Here is the pattern and the implementation.
mcp-productivityMCP 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-productivityStop Building Your AI Assistant Three Times
Most products build the AI assistant separately for web, bot, and API. We did too. Here is the single-entity, multi-adapter pattern we landed on and the gotchas we hit.
Stop Paywalling Your AI Features — Use a Quota Instead
A 402 on the first AI request kills activation. We replaced our hard paywall with a weekly weighted-token quota. Here is the design, the implementation, and what it did to the funnel.
telegram-task-managementTelegram Bots for Task Management — A 2026 Practitioner's Guide
Most Telegram task bots are glorified todo lists. Real task management needs boards, members, statuses, filters, and agent integration. Here's what actually works.
mcp-productivityMCP vs REST API: Which Should Your AI Agent Use in 2026?
MCP and REST solve different problems. REST serves integrations; MCP serves agents. Here's when to use each, and the pattern for shipping both from one codebase.
mcp-productivityConnect Cursor to Your Task Tracker via MCP (2026 Guide)
Step-by-step: connect Cursor to Kangram's MCP server in under 2 minutes. Create tasks, move cards, and query your board with natural language.
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-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.
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.