update_credential · Databricks Permissions MCP Server MCP

WHAT IT DOES

What update_credential does on Databricks Permissions MCP Server

AI agents use update_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_credential needs a policy

This tool modifies credentials reversibly—the changes can be undone by updating again with prior values. It does not execute code, delete irreversibly, or move money. However, severity is elevated to 'high' because credential compromise could grant unauthorized access to Databricks resources and sensitive systems, and an agent misusing this tool could alter credentials used by other services, causing substantial…

From the tool's definition Tool name is 'update_credential' with parameters including 'new_name' and 'credential_info', indicating modification of existing credential data.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

update_credential Rate-limited

update_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_credential": {
      "limits": [
        {
          "counter": "update_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_credential

What does the update_credential tool do? +

Update a credential with parameters: name (required), new_name (optional), credential_info (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_credential? +

Register the Databricks Permissions MCP Server MCP server in PolicyLayer and add a rule for update_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_credential? +

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

Can I rate-limit update_credential? +

Yes. Add a rate_limit block to the update_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_credential completely? +

Set action: deny in the PolicyLayer policy for update_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_credential? +

update_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.