Medium Risk

create_entity

Create a new Dataverse table (entity) with specified attributes

How to control create_entity ↓

What create_entity does on Dataverse

AI agents use create_entity to create or update resources in Dataverse — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Dataverse environment.

Medium Risk

Why create_entity needs a policy

Creating a new entity is a Write operation because it creates a persistent data structure in the Dataverse environment. While reversible (the entity could theoretically be deleted), it represents a significant structural modification to the data model and could have broad implications across the system.

From the tool's definition Tool creates a new Dataverse table (entity) with specified attributes. This is a data structure creation operation that modifies the schema of the Dataverse environment.

Documented attack patterns abuse exactly the kind of access create_entity gives an agent:

How to control create_entity

PolicyLayer is an MCP gateway — it sits between your AI agents and Dataverse, and nothing reaches the server without passing your rules. This is the rule we recommend for create_entity:

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "create_entity": {
      "limits": [
        {
          "counter": "create_entity_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

create_entity 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.

  1. Create a free account and register Dataverse — nothing to install.
  2. Add this policy — paste it, or build it visually.
  3. Point your MCP client (Claude, Cursor, anything) at your gateway URL.
LIMIT THIS TOOL →

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Related tools and policies

Go deeper

Questions about create_entity

What does the create_entity tool do? +

Create a new Dataverse table (entity) with specified attributes. It is categorised as a Write tool in the Dataverse MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on create_entity? +

Register the Dataverse MCP server in PolicyLayer and add a rule for create_entity: 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. Nothing to install.

What risk level is create_entity? +

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

Can I rate-limit create_entity? +

Yes. Add a rate_limit block to the create_entity 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 create_entity completely? +

Set action: deny in the PolicyLayer policy for create_entity. 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 create_entity? +

create_entity is provided by the Dataverse MCP server (rededis/dataverse-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Dataverse tool call.

Start from Dataverse, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

Free to start. No card required.

22 Dataverse tools catalogued and risk-classified — across an index of 43,000+ MCP servers.

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