MCP use case

Give your AI agent a real backlog, not a prompt full of tasks

Coding agents are good at fixing bugs and terrible at knowing which bug to fix. Pasting tickets into prompts doesn't scale and goes stale the moment a human re-prioritizes. Over MCP, the agent reads the live backlog itself: what's open, what's critical, what's assigned to it — then works the queue and writes its progress back.

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agent — working the tiqzen backlog 5 tools

The agent workflow

  1. 1

    Scope a key to one project

    Create an API key limited to the project the agent owns. Isolation is enforced server-side, per key.

  2. 2

    Connect the agent over MCP

    Point Claude Code, Cursor or any MCP-compatible agent at the Tiqzen MCP server with that key.

  3. 3

    Let the agent pull its queue

    The agent calls list_tickets to find work — filtered by status and severity — instead of being spoon-fed tasks.

  4. 4

    Close the loop automatically

    As the agent fixes issues it calls update_ticket to move status, reassign, or lower severity — the backlog stays truthful.

Same board, new teammate

Agent updates land on the board humans watch

An autonomous agent with workspace-wide write access is a liability — so every key is scoped to its projects at the API layer. The agent works its lane, moves its tickets, and the team sees it happen in real time.

Backlog · 4

STO-482 HIGH
STO-490 LOW

In progress · 2

STO-488 MD

Done · 7

STO-471
STO-495 PR merged

Agents pull their queue

Agents pull work by severity instead of waiting for assignment.

Auditable updates

Status changes are auditable — every update is attributed to the key.

One shared board

Humans keep the same board: agent updates appear in real time alongside the team's.

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Hand an agent its first project

Full MCP access ships in the Free plan — try an agent on a scoped project before rolling it out to the team.

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