Blog

Notes from the team.

Product5 min1 view

Why we gave Utter an MCP server, and what it changes

What the Model Context Protocol is in plain terms, why a project tracker is a good fit for it, and how an agent picks up your workspace without any glue code.

Product6 min1 view

Keep team chat next to your issues, not in another app

The case for project management with built-in chat: why splitting discussion from the tracker loses the thread, and how linking chat to issues fixes it.

Product7 min3 views

See your whole project as a mind map (and when it beats a nested list)

A nested list hides how work relates. A mind map shows it. When a map of your epics and stories helps, when a list is better, and how Utter's does it.

Guides9 min7 views

Two agents, one backlog: coordinating a triage agent and a coding agent with issue status as handoffs

A practical multi-agent workflow: custom board columns and status transitions as the handoff bus between a triage agent and a coding agent, with human review in the middle.

Guides7 min2 views

Let AI agents run your board over the REST API: authentication, scopes, and safe writes

A developer guide to giving an AI agent a scoped Utter API key so it can move cards and file issues without a big blast radius.

Comparisons9 min1 view

Which project management tools actually ship a first-party MCP server

Having AI features is not the same as shipping an MCP server. Here is how to tell first-party from community-built from none, with an honest checklist.

Guides7 min2 views

Turn a request form into a triaged issue automatically (no human inbox in the middle)

How to wire a public intake form to a tracked, classified issue: routing defaults, an issue.created automation, and an AI triage first pass.

Concepts11 min3 views

What is agentic project management? A plain-language guide with a working example

A copilot waits for your prompt. An agent acts on an event. Here is the perceive-plan-act-check loop explained, with one real end-to-end run inside Utter.

Guides8 min4 views

Give your AI agent a knowledge base: connect your docs so it answers from your project, not the internet

How to give an AI agent access to your company docs, so it grounds answers in your workspace instead of guessing, using RAG exposed through MCP.