This record as markdown: /tools/adbutler/create-user-db.md
What create_user_db does on AdButler
AI agents use create_user_db to create or update resources in AdButler, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your AdButler environment.
| Parameter | Type | Required | Description |
|---|---|---|---|
name | string | — | User database name |
id_field_name | string | — | Name of the field to use as primary user identifier |
Parameters from the server's own tool schema.
Why create_user_db is rated Medium
This tool creates new data structures (a user database) but does not irreversibly destroy data or execute arbitrary operations. It is a write operation that modifies the system state by adding a new resource. Severity is medium because unauthorized database creation could impact system organization and storage, but the effect is contained and reversible.
From the tool's definition Tool name 'create_user_db' and description 'Create a new user database' indicate data creation. The action creates a new database structure for user data, which is reversible (can be deleted or dropped).
Attacks that exploit this kind of access
The rule that runs create_user_db safely
PolicyLayer is an MCP gateway: it sits between your AI agents and AdButler, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For create_user_db, this is the rule to start with:
create_user_db 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.
The button opens the PolicyLayer dashboard: create your workspace, connect AdButler, apply this rule, and every create_user_db call is checked against it from then on.
Questions about create_user_db
Create a new user database. It is categorised as a Write tool in the AdButler MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
create_user_db accepts 2 parameters: name, id_field_name. 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 create_user_db: 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.
create_user_db is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the create_user_db 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 create_user_db. 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.
create_user_db 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.
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