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MCP use cases

Real people workflows, built on Taito.ai MCP

Every action inside Taito.ai — reading records, generating documents, running approvals, closing offboarding — is available over MCP. Bring your own AI, wire in the tools you already run, and the workflow reads live records instead of a stale export.

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A grid of tool tiles — Claude, Slack, Linear, HubSpot, Notion, Fortnox, Lovable, Xero, Deel, ChatGPT, Ashby, and n8n — arranged around a central Taito.ai hub badged with "MCP". Taito.ai is the source of truth; every tool on the grid connects to it over MCP.

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Explore use cases

  • Engineering performance reviews, grounded in Linear
    Performance

    Engineering performance reviews, grounded in Linear

    Every claim in the draft points at a real issue — shipped work, PR reviews, and cycle history pulled live from Linear.

    • Claude
    • Linear
  • GTM performance reviews, grounded in HubSpot
    Performance

    GTM performance reviews, grounded in HubSpot

    Quota is the easy part. Claude pulls the deals behind the number — cycle length, expansion, forecast drift — straight from HubSpot.

    • Claude
    • HubSpot
  • Ask HR anything, in Slack
    Employee experience

    Ask HR anything, in Slack

    Time-off balances, policy answers, headcount lookups — answered from the live record in a DM, scoped to the asker.

    • Slack
    • Claude
  • Team availability, posted to Slack every Monday
    Employee experience

    Team availability, posted to Slack every Monday

    Every Monday the Taito.ai app posts approved leave, work-from-home days, and public holidays to #general, with coverage gaps flagged.

    • Slack
  • Payroll variance report before you send it
    Payroll & finance

    Payroll variance report before you send it

    Claude assembles the month’s pre-payroll ledger, diffs it against last month, and hands you a CSV with the outliers flagged.

    • Claude
  • Ship a people dashboard in Lovable
    Custom apps & analytics

    Ship a people dashboard in Lovable

    Point Lovable at the Taito.ai MCP server and build the internal app your people team actually wants — no backend to write.

    • Lovable

Why MCP

One source of truth, any surface

Taito.ai holds the records — performance, time off and attendance, documents, the org graph — and MCP exposes every one of them, along with every action the people agents can take.

Live data, no exports.

MCP reads the current record every time — so the answer matches what the app would show you.

Your permissions travel with you.

Anything the AI can see, the calling user could already see. Every access is logged, every action is scoped.

Bring the tool you already use.

Claude, Slack, HubSpot, Linear, Lovable, ChatGPT — anything MCP-native. Taito.ai is the source of truth; you pick the surface.

Frequently asked questions

What is MCP?
Model Context Protocol — a standard for giving AI tools like Claude and ChatGPT structured access to your systems. Taito.ai runs an MCP server that exposes the full people graph and every action the app can perform, with your permissions applied.
Do I need a developer?
For the ready-made workflows on this page, no — just paste a prompt into Claude or configure the Taito.ai app. Custom apps in Lovable, or stringing several tools together, go faster with someone who’s comfortable in a workflow builder.
Which AI tools does Taito.ai MCP work with?
Any MCP-compatible client: Claude Desktop, Claude in Slack, ChatGPT MCP, Cursor, and Lovable’s MCP support. Anything that speaks MCP can connect — the clients above are the ones we test against.
What can the AI see?
Only what your user permissions allow. Field-level access, integration allowlists, and audit logs all apply — the AI inherits the caller’s permissions and can never access more than the person running it. When a workflow needs a human decision, it escalates to one.