Re-download cached resources to get the latest data.
AI agents use refresh_cache to create or update resources in Ontario Data — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Ontario Data environment.
This tool overwrites existing cached data with freshly downloaded versions. It is a reversible write operation (cache can be refreshed again), not a destructive permanent deletion. It modifies stored state by replacing cached files, making Write the most appropriate category.
From the tool's definition Re-download cached resources to get the latest data
Attacks that exploit this kind of access
Re-download cached resources to get the latest data. It is categorised as a Write tool in the Ontario Data MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Ontario Data MCP server in PolicyLayer and add a rule for refresh_cache: 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 Ontario Data. Nothing to install.
refresh_cache 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 refresh_cache 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 refresh_cache. 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.
refresh_cache is provided by the Ontario Data MCP server (sprine/ontario-data-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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