retrieve_multiple_collaborators

THE RISK

Low Risk

Why retrieve_multiple_collaborators needs a policy

This tool fetches user/collaborator information from a Storyblok space without modifying, deleting, or executing any operations. It is purely informational. Severity is low because collaborator lists are typically non-sensitive metadata within a space, though confidence is high due to clear retrieval semantics.

From the tool's definition Tool name 'retrieve_multiple_collaborators' and description 'Retrieves a paginated list of collaborators' indicate a query/retrieval operation with no side effects. The word 'retrieves' and pagination pattern are characteristic of Read operations.

Documented attack patterns abuse exactly the kind of access retrieve_multiple_collaborators gives an agent:

POLICY

How to control retrieve_multiple_collaborators

PolicyLayer is an MCP gateway — it sits between your AI agents and Storyblok MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for retrieve_multiple_collaborators:

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "retrieve_multiple_collaborators": {}
  }
}

retrieve_multiple_collaborators is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.

Create a free account and register Storyblok MCP Server — nothing to install.
Add this policy — paste it, or build it visually.
Point your MCP client (Claude, Cursor, anything) at your gateway URL.

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EXPLORE

Related tools and policies

More Storyblok MCP Server tools

Destructive bulk_delete_stories Deletes multiple stories in Storyblok. Destructive delete_access_token Delete an access token from the current Storyblok space using the Management API. Destructive delete_approval Deletes an approval from a specified Storyblok space. Destructive delete_asset Deletes an asset from Storyblok. Destructive delete_asset_folder Delete an asset folder from the current Storyblok space. Destructive delete_branch Deletes a branch (pipeline) by its ID in a Storyblok space. Destructive delete_collaborator Deletes a collaborator from a specified Storyblok space. Destructive delete_comment Deletes a comment from a discussion via the Storyblok Management API.

All 159 Storyblok MCP Server tools →

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Go deeper

The MCP Attack Database → Documented attack patterns against MCP deployments — and the policies that stop them.
Data exfiltration → How read access becomes an exfiltration channel when chained with untrusted content.
MCP token cost → What connecting this server costs in context-window tokens on every request.
Rate Limiting MCP Tool Calls: A Practical Guide →
MCP Security: Why Prompt Guardrails Aren't Enough →

FAQ

Questions about retrieve_multiple_collaborators

What does the retrieve_multiple_collaborators tool do? +

Retrieves a paginated list of collaborators (users) in a specified Storyblok space. It is categorised as a Read tool in the Storyblok MCP Server MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on retrieve_multiple_collaborators? +

Register the Storyblok MCP Server MCP server in PolicyLayer and add a rule for retrieve_multiple_collaborators: 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 Storyblok MCP Server. Nothing to install.

What risk level is retrieve_multiple_collaborators? +

retrieve_multiple_collaborators is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit retrieve_multiple_collaborators? +

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

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

retrieve_multiple_collaborators is provided by the Storyblok MCP Server MCP server (kiran1689/storyblok-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 Storyblok MCP Server tool call.

Start from Storyblok MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

CHECK YOUR STACK →