AI agents call list_user_attributes to retrieve information from AdButler without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
limit | number | — | Max results to return (default 100, max 100) |
offset | number | — | Pagination offset |
user_db_id | number | Yes | User database ID |
Parameters from the server's own tool schema.
This tool retrieves information from a user database without creating, modifying, or deleting any data. It is a standard read operation that poses minimal risk even if invoked by an AI agent, as it only exposes existing metadata about user attributes. The low severity reflects that listing attributes is informational and has no side effects.
From the tool's definition Tool name 'list_user_attributes' and description 'List all user attributes in a user database' indicate a query/retrieval operation with no modification of data.
Risk signalsBulk/mass operation — affects multiple targets
Attacks that exploit this kind of access
List all user attributes in a user database. It is categorised as a Read tool in the AdButler MCP Server, which means it retrieves data without modifying state.
list_user_attributes accepts 3 parameters: limit, offset, user_db_id. Required: user_db_id. The full parameter table on this page comes from the server's own tool schema.
Register the AdButler MCP server in PolicyLayer and add a rule for list_user_attributes: 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 AdButler. Nothing to install.
list_user_attributes is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the list_user_attributes 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.
Set action: deny in the PolicyLayer policy for list_user_attributes. 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.
list_user_attributes is provided by the AdButler MCP server (adbutler/mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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