Get details of a storage credential with parameter: name (required)
AI agents call get_storage_credential to retrieve information from Databricks Permissions MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves credential details by name. While it is read-only in nature, storage credentials provide access to sensitive cloud storage systems (S3, ADLS, etc.), so unauthorized disclosure of their details poses a medium-severity risk in the context of an AI agent that could leak or misuse this information.
From the tool's definition Tool name is 'get_storage_credential' and description states 'Get details of a storage credential', which is a retrieval operation with no side effects.
Attacks that exploit this kind of access
Get details of a storage credential with parameter: name (required). It is categorised as a Read tool in the Databricks Permissions MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Databricks Permissions MCP Server MCP server in PolicyLayer and add a rule for get_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.
get_storage_credential 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_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.
Set action: deny in the PolicyLayer policy for get_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.
get_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.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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