set_project_color_settings

Set project bits per channel (8, 16, or 32) and optionally the working color space.

SERVERAe SOURCE@synthetic-ai/ae-mcp

Medium RISK CLASS

Category Write

Parameters 50 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/synthetic-ai-ae-mcp/set-project-color-settings.md

WHAT IT DOES

What set_project_color_settings does on Ae

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

Parameter	Type	Required	Description
`save`	boolean	—
`timeoutMs`	number	—
`projectPath`	string	—
`workingSpace`	string	—	Optional color space name, e.g. 'sRGB IEC61966-2.1'.
`bitsPerChannel`	number	—	8, 16, or 32.

Parameters from the server's own tool schema.

RISK

Why set_project_color_settings is rated Medium

An AI agent can call set_project_color_settings faster than any human can review: one bad instruction and it creates or modifies resources in Ae by the hundred, each call as confident as the last.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs set_project_color_settings safely

PolicyLayer is an MCP gateway: it sits between your AI agents and Ae, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For set_project_color_settings, this is the rule to start with:

set_project_color_settings Rate-limited

set_project_color_settings 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": {
    "set_project_color_settings": {
      "limits": [
        {
          "counter": "set_project_color_settings_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Ae, apply this rule, and every set_project_color_settings call is checked against it from then on.

FAQ

Questions about set_project_color_settings

What does the set_project_color_settings tool do? +

Set project bits per channel (8, 16, or 32) and optionally the working color space. It is categorised as a Write tool in the Ae MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

What parameters does set_project_color_settings accept? +

set_project_color_settings accepts 5 parameters: save, timeoutMs, projectPath, workingSpace, bitsPerChannel. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on set_project_color_settings? +

Register the Ae MCP server in PolicyLayer and add a rule for set_project_color_settings: 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 Ae. Nothing to install.

What risk level is set_project_color_settings? +

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

Can I rate-limit set_project_color_settings? +

Yes. Add a rate_limit block to the set_project_color_settings 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 set_project_color_settings completely? +

Set action: deny in the PolicyLayer policy for set_project_color_settings. 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 set_project_color_settings? +

set_project_color_settings is provided by the Ae MCP server (@synthetic-ai/ae-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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