AI agents call list_cluster_libraries to retrieve information from Databricks MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool only queries and retrieves the list of installed libraries on a Databricks cluster. It has no side effects, does not modify any state, and poses minimal security risk if called by an AI agent. It falls squarely into the Read category (retrieves or queries data; no side effects).
From the tool's definition Tool name is 'list_cluster_libraries' and description states 'List libraries for a cluster' — a straightforward read/query operation that retrieves information without modification.
Documented attack patterns abuse exactly the kind of access list_cluster_libraries gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Databricks MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for list_cluster_libraries:
{
"version": "1",
"default": "deny",
"tools": {
"list_cluster_libraries": {}
}
}list_cluster_libraries is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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List libraries for a cluster. It is categorised as a Read tool in the Databricks MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Databricks MCP Server MCP server in PolicyLayer and add a rule for list_cluster_libraries: 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.
list_cluster_libraries 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 list_cluster_libraries 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 list_cluster_libraries. 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.
list_cluster_libraries is provided by the Databricks MCP Server MCP server (markov-kernel/databricks-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Databricks MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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38 Databricks MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.