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Connect AI agents

Resorcerer exposes your workspace over a Model Context Protocol (MCP) server, so an AI assistant can read your organizational structure — and, if you let it, change it — as a first-class participant rather than by being pasted screenshots.

Questions like “which teams have no senior engineer?”, “what would this restructure cost?”, or “draft a model with these four squads” become things an agent can actually answer, because it can traverse the real data.

Connecting

Section titled “Connecting”

The MCP button in the app header gives you the connection details for your instance, ready to paste into whichever client you use. For the hosted app the endpoint is:

https://app.resorcerer.ai/api/mcp

Authorizing is a browser round-trip: your client sends you to Resorcerer, you confirm the request while signed in, and the client receives its credential. Some clients show a short code to confirm instead — same flow, same confirmation screen.

Alternatively, create an access token under My Settings → Access Tokens and give it to the client directly. That’s the route for anything headless, such as a scheduled job or a CI step, where nobody’s there to click a confirmation. Tokens are scoped when you create them, so a token that only needs to read should only be able to read.

What an agent can do

Section titled “What an agent can do”

Access is scoped by the credential — an agent is never more privileged than whoever authorized it, and per-model permissions apply exactly as they do in the UI.

Area Tools
Models List, read, create, update, and delete models; read and set their timeline position.
Units Read the hierarchy; create, update, move, and delete units.
Positions List and read slots, create them by id or by attribute name, update them, set which units they belong to, assign and unassign people.
People List, search, read, create, and update people; place them in positions.
Attributes Read and manage roles, levels, locations, and companies.
Analysis Analyse a model for problems, apply the standard fixes, and compare two models.
Organization Read the current organization’s details.

Read-only tools are marked as such, so a client that distinguishes them can be configured to ask before anything is written.

Working with an agent

Section titled “Working with an agent”

A few things that make the difference between an agent that helps and one that makes a mess:

  • Give it a draft, not your live model. Copy your structure and point the agent at the copy. You review the difference and merge what you want.
  • Protect what matters. A protected model refuses direct edits, from an agent as much as from a person.
  • Set up your attributes first. Roles, levels, locations, and companies give an agent the vocabulary to describe positions precisely. Without them it can only build anonymous headcount.
  • Ask it to check its work. The analysis tools are the same ones behind the Problems view, so an agent can review what it just built.
Section titled “Related”