Delete computational metadata for a given tensor descriptor.
AI agents call delete_computational_metadata to permanently remove resources in Tensorus MCP — typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
This tool irreversibly removes computational metadata associated with a tensor. While not deleting the tensor itself, deletion of metadata is a destructive action that cannot be undone and could break lineage tracking, provenance information, or computational history. In a tensor database context, metadata loss could compromise data integrity and reproducibility.
From the tool's definition Tool name includes 'delete' and description states 'Delete computational metadata for a given tensor descriptor.' The verb 'delete' is explicitly destructive.
Attacks that exploit this kind of access
Delete computational metadata for a given tensor descriptor. It is categorised as a Destructive tool in the Tensorus MCP MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the Tensorus MCP server in PolicyLayer and add a rule for delete_computational_metadata: 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 Tensorus MCP. Nothing to install.
delete_computational_metadata 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 delete_computational_metadata 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 delete_computational_metadata. 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.
delete_computational_metadata is provided by the Tensorus MCP server (tensorus/mcp). 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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