databricks_put_secret
A write tool on the Databricks MCP server.
This record as markdown: /tools/io-github-pramodbhatofficial-databricks-sdk-mcp/databricks-put-secret.md
What databricks_put_secret does on Databricks MCP Server
AI agents use databricks_put_secret to create or update resources in Databricks MCP Server, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Databricks MCP Server environment.
Why databricks_put_secret is rated Medium
The 'put_secret' operation creates or overwrites a secret value in Databricks' secret management system. This is a Write action (reversible via deletion) rather than Destructive. However, severity is high because misuse could expose or overwrite sensitive credentials, and secrets are critical infrastructure assets.
From the tool's definition Tool name is 'databricks_put_secret' which performs a PUT operation on secrets. The 'put' verb indicates creation or modification of data. No description provided, but based on naming convention and Databricks API patterns, this stores or updates secret data.
Attacks that exploit this kind of access
The rule that runs databricks_put_secret safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Databricks MCP Server, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For databricks_put_secret, this is the rule to start with:
databricks_put_secret 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.
The button opens the PolicyLayer dashboard: create your workspace, connect Databricks MCP Server, apply this rule, and every databricks_put_secret call is checked against it from then on.
Questions about databricks_put_secret
databricks_put_secret is a write tool on the Databricks MCP Server MCP server. It is categorised as a Write tool in the Databricks MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Databricks MCP Server MCP server in PolicyLayer and add a rule for databricks_put_secret: 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 MCP Server. Nothing to install.
databricks_put_secret is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the databricks_put_secret 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 databricks_put_secret. 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.
databricks_put_secret is provided by the Databricks MCP Server MCP server (pypi:databricks-sdk-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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