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 existing Dataverse table metadata and configuration settings in a reversible manner—such changes can be undone by updating the properties again. This is a Write operation rather than Execute because it does not run arbitrary code or trigger dependent external operations; it simply updates predefined table properties.
From the tool's definition Tool name is 'update_dataverse_table' and description states it 'Updates the properties and configuration of an existing Dataverse table' and 'modify table settings like display names, descriptions, or feature enablement'.
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-mcp2). 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.
Teams ship this data inside their own products. See what a licence covers →