update_datahub_dataset

SERVERDoit SOURCE@doitintl/doit-mcp-server

Medium RISK CLASS

Category Write

Parameters 41 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/doit/update-datahub-dataset.md

WHAT IT DOES

What update_datahub_dataset does on Doit

AI agents use update_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 to update (required). Used for identification; the name cannot be changed.
`logoName`	string	—	Preset logo name: anthropic, atlassian, aws, azure, bifrost, chatgpt, cloudflare, copilot, figma, gcp, github, gitlab, hotjar, jira, litellm, miro, notion, slac
`description`	string	—	New description. Omit to keep the stored value; an empty string clears it.
`displayName`	string	—	Display name (up to 64 characters after trimming, no control characters). Omit to keep; an empty string clears it. Does not rename the dataset.

Parameters from the server's own tool schema.

RISK

Why update_datahub_dataset is rated Medium

An AI agent can call update_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

RECOMMENDED RULE

The rule that runs update_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 update_datahub_dataset, this is the rule to start with:

update_datahub_dataset Rate-limited

update_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.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "update_datahub_dataset": {
      "limits": [
        {
          "counter": "update_datahub_dataset_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Doit, apply this rule, and every update_datahub_dataset call is checked against it from then on.

FAQ

Questions about update_datahub_dataset

What does the update_datahub_dataset tool do? +

Use this when the user wants to modify an existing DataHub dataset's description, displayName, or logoName. The dataset name identifies the dataset and cannot be changed. Omitted fields are kept; empty strings clear the supplied fields. At least one updatable field is required. Changes apply immediately. Do NOT use this for creating datasets (use create_datahub_dataset) or listing datasets (use list_datahub_datasets). 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.

What parameters does update_datahub_dataset accept? +

update_datahub_dataset accepts 4 parameters: name, logoName, description, displayName. Required: name. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on update_datahub_dataset? +

Register the Doit MCP server in PolicyLayer and add a rule for update_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.

What risk level is update_datahub_dataset? +

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

Can I rate-limit update_datahub_dataset? +

Yes. Add a rate_limit block to the update_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.

How do I block update_datahub_dataset completely? +

Set action: deny in the PolicyLayer policy for update_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.

What MCP server provides update_datahub_dataset? +

update_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.

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