databricks_destroy_execution_context
A destructive tool on the Databricks MCP server.
This record as markdown: /tools/io-github-pramodbhatofficial-databricks-sdk-mcp/databricks-destroy-execution-context.md
What databricks_destroy_execution_context does on Databricks MCP Server
AI agents call databricks_destroy_execution_context to permanently remove resources in Databricks MCP Server, typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
Why databricks_destroy_execution_context is rated Critical
The tool name 'databricks_destroy_execution_context' strongly suggests permanent termination of an execution context resource. Although the description is empty and cannot provide additional detail, the semantic meaning of 'destroy' in API terminology typically refers to irreversible removal. This is more severe than Write (which is reversible) and warrants Destructive classification.
From the tool's definition Tool name contains 'destroy' which indicates irreversible deletion or termination of a resource (execution context). The verb 'destroy' is commonly associated with destructive operations that cannot be undone.
Attacks that exploit this kind of access
The rule that runs databricks_destroy_execution_context 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_destroy_execution_context, this is the rule to start with:
databricks_destroy_execution_context is removed from the agent's tool list entirely, so the agent never calls it. The rest of the server keeps working.
The button opens the PolicyLayer dashboard: create your workspace, connect Databricks MCP Server, apply this rule, and every databricks_destroy_execution_context call is checked against it from then on.
Questions about databricks_destroy_execution_context
databricks_destroy_execution_context is a destructive tool on the Databricks MCP Server MCP server. It is categorised as a Destructive tool in the Databricks MCP Server MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the Databricks MCP Server MCP server in PolicyLayer and add a rule for databricks_destroy_execution_context: 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_destroy_execution_context is a Destructive tool with critical risk. Critical-risk tools should be blocked by default and only enabled with explicit human approval.
Yes. Add a rate_limit block to the databricks_destroy_execution_context 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_destroy_execution_context. 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_destroy_execution_context 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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