update_storage_credential

WHAT IT DOES

What update_storage_credential does on Databricks Permissions MCP Server

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

WHY IT NEEDS A POLICY

Why update_storage_credential needs a policy

This tool modifies cloud storage credentials (AWS IAM roles, Azure service principals) which are security-sensitive configurations. While reversible (not Destructive), the ability to change storage credentials grants access control over data lake resources and could redirect data access or exfiltrate data if misused by an unauthorized agent.

From the tool's definition Tool description explicitly states 'Update a storage credential' with parameters for modifying storage credentials (new_name, aws_iam_role, azure_service_principal, comment). The 'update' verb indicates modification of existing data.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

update_storage_credential Rate-limited

update_storage_credential 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_storage_credential": {
      "limits": [
        {
          "counter": "update_storage_credential_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches Databricks Permissions MCP Server, so you can run agents against it safely.

FAQ

Questions about update_storage_credential

What does the update_storage_credential tool do? +

Update a storage credential with parameters: name (required), new_name (optional), aws_iam_role (optional), azure_service_principal (optional), comment (optional). It is categorised as a Write tool in the Databricks Permissions MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on update_storage_credential? +

Register the Databricks Permissions MCP Server MCP server in PolicyLayer and add a rule for update_storage_credential: 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 Databricks Permissions MCP Server. Nothing to install.

What risk level is update_storage_credential? +

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

Can I rate-limit update_storage_credential? +

Yes. Add a rate_limit block to the update_storage_credential 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_storage_credential completely? +

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

update_storage_credential is provided by the Databricks Permissions MCP Server MCP server (justtryai/databricks-permissions-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.