Medium Risk

raycast_workflows

Create and manage Raycast workflows and automations

Part of the Raycast server.

raycast_workflows can modify Raycast data, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

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AI agents use raycast_workflows to create or modify resources in Raycast. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.

Without a policy, an AI agent could call raycast_workflows repeatedly, creating or modifying resources faster than any human could review. PolicyLayer's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Raycast.

Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "raycast_workflows": {
      "limits": [
        {
          "counter": "raycast_workflows_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

See the full Raycast policy for all 3 tools.

Get this rule live on your own Raycast server in minutes. PolicyLayer enforces it on every call, before it runs.

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These attack patterns abuse exactly the kind of access raycast_workflows gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so raycast_workflows only ever does what you allow.

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Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.

What does the raycast_workflows tool do? +

Create and manage Raycast workflows and automations. It is categorised as a Write tool in the Raycast MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on raycast_workflows? +

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

What risk level is raycast_workflows? +

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

Can I rate-limit raycast_workflows? +

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

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

raycast_workflows is provided by the Raycast MCP server (ExpertVagabond/raycast-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Raycast tool call.

Deterministic rules across all 3 Raycast tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

Free to start. No card required.

4,600+ MCP servers and 31,000+ tools scanned and risk-classified.

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