Examples of how to use Kanera with AI

Once an AI agent is connected to Kanera through MCP, it can see your real work across boards and act on it. That is the difference between an assistant that guesses from pasted text and one that reasons over live workspace data — cards, assignees, due dates, labels, custom fields, notes, comments, and activity.

The examples below are real workflows. Each shows what to ask, why the agent can do it, and what you get back. Most work with a Read key; the ones that change Kanera are marked and need a Write key.

Plan the work, then track it as the code lands

This is the workflow that shows what MCP really unlocks: a coding agent that plans in Kanera, then updates the same card as it does the actual work. Because the agent's editor and Kanera are both reachable through MCP, the tracking card stays accurate on its own — no one switches tabs to tick boxes.

Step 1 — plan into the card. Point the agent at the work and ask it to record the plan where the team can see it:

"Read this repo and the 'Upgrade dependencies' card. Write an implementation plan into the card description, and add a checklist with one item per project that needs updating." (Write key)

The agent inspects the codebase, drafts a plan, updates the card description with it, and builds a checklist item per project. Now the card is the source of truth for the effort, not a throwaway chat.

Step 2 — do the work, and let the agent close out its own checklist. In the same session (or a later one), have the agent implement the change across the projects:

"Work through the checklist on that card. Update the dependencies in each project, and as each one builds and passes, mark its checklist item complete." (Write key)

As the agent finishes each project, it checks off the matching item on the tracking card. Anyone watching the board sees real progress in real time — the checklist fills in as the code actually ships, not when someone remembers to update it. Every check-off is recorded against the API key, so the card doubles as an audit trail of what the agent did and when.

This "plan into the card, then report progress back to the card" loop works for any multi-step effort — dependency upgrades, migrations, refactors, or a feature broken into tasks.

Morning triage in one prompt

"Show me everything assigned to me across the workspace, grouped by urgency. Flag anything overdue, anything with no due date, and anything that hasn't moved in a week."

Because Assigned Work spans every board in a workspace, the agent pulls your whole queue at once — no board-hopping. It sorts by due date, cross-references activity to find stale cards, and surfaces the two or three things that actually need you today. This is the single most useful daily use of Kanera MCP.

Instant standup update

"Prepare my standup: what I closed yesterday, what I'm working on today, and anything blocked."

The agent reads recent activity and your assigned cards, then drafts a tight update. Paste it into Slack or read it off. The built-in prepare_standup_update prompt does exactly this if your client surfaces prompts.

Board health check for a manager

"Summarize the Roadmap board. Call out blockers, stale cards, cards with no owner, and what's likely to slip this sprint."

An agent with workspace read access can review a board the way a lead would — not just listing cards, but reasoning about risk: unassigned work in the current list, cards sitting untouched, missing due dates, checklists that stalled. Great before a planning meeting.

Turn a meeting into cards

"Here are my notes from the customer call. Draft cards for each action item with a title, a Markdown description, and a suggested list. Show me the drafts first — don't create anything yet."

The agent proposes structured cards. You review, edit, then say:

"Create those in the Intake list and label them customer-request." (Write key)

This "draft, review, apply" pattern is the safest way to let an agent create work: you always see the plan before anything lands in Kanera.

Cross-board search that understands context

"Find every card, note, or comment mentioning the payments migration, and tell me which are still open."

MCP search covers cards, notes, comments, and attachment filenames across the workspace. The agent doesn't just return matches — it groups them, tells you what's done versus open, and points you at the threads that matter.

Cleanup and hygiene

"List assigned cards in this workspace with no due date and no labels, and suggest a priority label and a realistic due date for each based on the description." (suggestions are read-only; applying them needs a Write key)

The agent proposes metadata so your board stays reportable. Approve the batch and it can set labels, due dates, and custom field values in one pass.

Keep a card current from an outside discussion

"Add a comment to the 'SSO rollout' card summarizing this email thread, and move it to In Progress." (Write key)

The agent writes a concise summary comment and updates the card's list, so the board reflects reality without anyone re-typing status by hand. Every change is recorded against the API key, so it stays auditable.

Workload balancing across a team

"Across this workspace, show open assigned work per person. Who's overloaded, who has room, and which cards could reasonably move?"

Because assignments and cards are workspace-scoped, the agent can reason about the whole team's load at once and propose rebalancing — then, with your approval, reassign specific cards. (reassigning needs a Write key)

Draft from a note you already wrote

"Turn my 'Q3 onboarding revamp' note into a card with a clear title and a Markdown description that lays the steps out as a checklist."

The draft_card_from_notes prompt turns loose thinking in a Kanera note into structured, actionable work.

Tips for getting the most out of it

• Start read-only. Use a Read key for triage, summaries, and search until you trust the workflow, then move to Write for changes.
• Ask for a plan first. For anything that changes Kanera, request drafts or a proposed plan, review it, then say "apply it."
• Be specific about scope. Name the board, list, workspace, or person so the agent targets the right data.
• Let it work across boards. The biggest wins come from questions a single-board view can't answer — workload, cross-project search, and portfolio-level status.

For setup, API keys, scopes, and the full list of resources and actions the agent can use, see the AI MCP overview.