optimize_canvases · Whiteboard MCP: Risk & Policy

WHAT IT DOES

What optimize_canvases does on Whiteboard

AI agents use optimize_canvases to create or update resources in Whiteboard — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Whiteboard environment.

WHY IT NEEDS A POLICY

Why optimize_canvases needs a policy

The tool modifies canvas state by compacting operation logs and creating snapshots. This is reversible in principle (the canvas data itself is preserved, just reorganized), and does not delete user-visible content or trigger external code execution. However, it does alter stored data structures.

From the tool's definition Tool performs 'compact Loro op-log history' and 'shallow-snapshot' operations on canvas data. While described as 'idempotent,' compacting operation logs modifies the internal state/structure of stored canvas data, which qualifies as a Write operation rather…

Risk signalsBulk/mass operation — affects multiple targets

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

optimize_canvases Rate-limited

optimize_canvases stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "optimize_canvases": {
      "limits": [
        {
          "counter": "optimize_canvases_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches Whiteboard, so you can run agents against it safely.

FAQ

Questions about optimize_canvases

What does the optimize_canvases tool do? +

Compact Loro op-log history (shallow-snapshot) on one canvas (slug given) or every canvas in the current workspace (slug omitted). Idempotent — returns reason. It is categorised as a Write tool in the Whiteboard MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on optimize_canvases? +

Register the Whiteboard MCP server in PolicyLayer and add a rule for optimize_canvases: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Whiteboard. Nothing to install.

What risk level is optimize_canvases? +

optimize_canvases is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit optimize_canvases? +

Yes. Add a rate_limit block to the optimize_canvases rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.

How do I block optimize_canvases completely? +

Set action: deny in the PolicyLayer policy for optimize_canvases. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.

What MCP server provides optimize_canvases? +

optimize_canvases is provided by the Whiteboard MCP server (kamiazya/whiteboard). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.