create_datahub_dataset
Use this when the user wants to create a new DataHub dataset. Changes apply immediately. Do NOT use this for viewing datasets (use list_datahub_datasets) or sending events (use send_datahub_events).
This record as markdown: /tools/doit/create-datahub-dataset.md
What create_datahub_dataset does on Doit
AI agents use create_datahub_dataset to create or update resources in Doit, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Doit environment.
| Parameter | Type | Required | Description |
|---|---|---|---|
name | string | Yes | The name of the dataset (required). Allowed characters: alphanumeric (0-9,a-z,A-Z), underscore (_), dash (-), and spaces between words. |
description | string | — | An optional description for the dataset. |
Parameters from the server's own tool schema.
Why create_datahub_dataset is rated Medium
An AI agent can call create_datahub_dataset faster than any human can review: one bad instruction and it creates or modifies resources in Doit by the hundred, each call as confident as the last.
Attacks that exploit this kind of access
The rule that runs create_datahub_dataset safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Doit, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For create_datahub_dataset, this is the rule to start with:
create_datahub_dataset 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 Doit, apply this rule, and every create_datahub_dataset call is checked against it from then on.
Questions about create_datahub_dataset
Use this when the user wants to create a new DataHub dataset. Changes apply immediately. Do NOT use this for viewing datasets (use list_datahub_datasets) or sending events (use send_datahub_events). It is categorised as a Write tool in the Doit MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
create_datahub_dataset accepts 2 parameters: name, description. Required: name. The full parameter table on this page comes from the server's own tool schema.
Register the Doit MCP server in PolicyLayer and add a rule for create_datahub_dataset: 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 Doit. Nothing to install.
create_datahub_dataset 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_datahub_dataset 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_datahub_dataset. 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_datahub_dataset is provided by the Doit MCP server (@doitintl/doit-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
More on Doit, and thousands of servers like it.
This server
Across the catalogue