This record as markdown: /tools/frontmcp/update-consent.md
What update-consent does on Frontmcp
AI agents use update-consent to create or update resources in Frontmcp, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Frontmcp environment.
Why update-consent is rated Medium
This tool modifies consent settings for vault entries, which is a reversible change to configuration or preference data. It does not delete data (Destructive), execute arbitrary code (Execute), move money (Financial), or merely retrieve data (Read).
From the tool's definition Tool name 'update-consent' and description 'Update consent settings for a vault entry' indicate modification of existing data (consent settings) in a vault system. The word 'Update' explicitly signals a write operation.
Attacks that exploit this kind of access
The rule that runs update-consent safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Frontmcp, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For update-consent, this is the rule to start with:
update-consent stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Frontmcp, apply this rule, and every update-consent call is checked against it from then on.
Questions about update-consent
Update consent settings for a vault entry. It is categorised as a Write tool in the Frontmcp MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Front MCP server in PolicyLayer and add a rule for update-consent: 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 Frontmcp. Nothing to install.
update-consent 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 update-consent 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 update-consent. 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.
update-consent is provided by the Front MCP server (agentfront/frontmcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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