Manually refresh enumeration values and user cache
AI agents invoke refresh_cache to trigger actions in Redmine MCP Server. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
Refreshing a cache is an active operation that re-fetches and overwrites cached data. It has no destructive or financial impact, doesn't modify primary data, but it does trigger an external operation (cache invalidation and reload) rather than simply reading data. Severity is low since misuse has minimal blast radius — at worst it causes a brief performance impact or stale-data flush.
From the tool's definition 'Manually refresh enumeration values and user cache' — triggers an external operation (cache refresh/reload)
Documented attack patterns abuse exactly the kind of access refresh_cache gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Redmine MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for refresh_cache:
{
"version": "1",
"default": "deny",
"tools": {
"refresh_cache": {
"limits": [
{
"counter": "refresh_cache_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}refresh_cache stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
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Manually refresh enumeration values and user cache. It is categorised as a Execute tool in the Redmine MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Redmine MCP Server 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 Redmine MCP Server. Nothing to install.
refresh_cache is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
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 Redmine MCP Server MCP server (snowild/redmine-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Redmine 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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35 Redmine MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.