Updates the properties and configuration of an existing Dataverse table. Use this to modify table settings like display names, descriptions, or feature enablement (activities, notes, auditing, etc.). Changes are published automatically.
AI agents use update_dataverse_table to create or update resources in Dataverse MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Dataverse MCP Server environment.
This tool modifies table properties and configuration settings in Dataverse, which are reversible changes. It does not delete data or execute arbitrary code—it updates schema metadata. While updates can affect system behavior through feature toggles (activities, notes, auditing), the changes remain reversible and controllable, placing this in Write rather than Execute or Destructive.
From the tool's definition Tool updates existing Dataverse table properties and configuration including display names, descriptions, and feature enablement settings. Description states 'Changes are published automatically,' indicating reversible modifications to table metadata.
Attacks that exploit this kind of access
Updates the properties and configuration of an existing Dataverse table. Use this to modify table settings like display names, descriptions, or feature enablement (activities, notes, auditing, etc.). Changes are published automatically. It is categorised as a Write tool in the Dataverse MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Dataverse MCP Server MCP server in PolicyLayer and add a rule for update_dataverse_table: 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 Dataverse MCP Server. Nothing to install.
update_dataverse_table 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 update_dataverse_table 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 update_dataverse_table. 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.
update_dataverse_table is provided by the Dataverse MCP Server MCP server (wizspdemo/dataverse-mcp3). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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