List CRM components (forms, views, workflows, business rules, calculated columns, plugins, …) that reference a given attribute. Use this when delete_attribute fails with error 0x8004f01f, or proactively before any destructive change. Returns a flat array of { component_type, component_type_name, ...
AI agents call get_attribute_dependencies to retrieve information from Dataverse without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool performs informational retrieval to help users understand what other components depend on an attribute. It is explicitly safe-by-design, intended to be called proactively before destructive changes to prevent errors. It has no capability to create, modify, delete, or execute actions; it only reads and reports existing relationships in the schema.
From the tool's definition Tool description explicitly states 'List CRM components' and 'Returns a flat array' of dependencies. The operation is a query/retrieval with no side effects—it uses the 'RetrieveDependenciesForDelete function' to inspect references before deletion, not to…
Documented attack patterns abuse exactly the kind of access get_attribute_dependencies gives an agent:
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 get_attribute_dependencies:
{
"version": "1",
"default": "deny",
"tools": {
"get_attribute_dependencies": {}
}
}get_attribute_dependencies is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
Free to start. No card required.
List CRM components (forms, views, workflows, business rules, calculated columns, plugins, …) that reference a given attribute. Use this when delete_attribute fails with error 0x8004f01f, or proactively before any destructive change. Returns a flat array of { component_type, component_type_name, object_id, name }; name is best-effort (resolved for common types — SystemForm, SavedQuery, Workflow, Report, WebResource, FieldSecurityProfile, AppModule, SDKMessageProcessingStep — null otherwise). Backed by the Dataverse RetrieveDependenciesForDelete function. It is categorised as a Read tool in the Dataverse MCP Server, which means it retrieves data without modifying state.
Register the Dataverse MCP server in PolicyLayer and add a rule for get_attribute_dependencies: 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.
get_attribute_dependencies is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the get_attribute_dependencies 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 get_attribute_dependencies. 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.
get_attribute_dependencies 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.
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.