Reload the current page
AI agents invoke reload to trigger actions in Autoconsent MCP. 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.
Reloading a page is a browser action with external side effects: it re-issues network requests, re-runs scripts, and may re-trigger consent dialogs or other stateful interactions. This fits Execute as it triggers an external operation whose effects depend on the current browser state.
From the tool's definition 'Reload the current page' — triggers a browser action that re-executes page load, network requests, and any page-level scripts
Attacks that exploit this kind of access
Reload the current page. It is categorised as a Execute tool in the Autoconsent MCP MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Autoconsent MCP server in PolicyLayer and add a rule for reload: 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 Autoconsent MCP. Nothing to install.
reload 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 reload 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 reload. 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.
reload is provided by the Autoconsent MCP server (noisysocks/autoconsent-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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