update_mandate
A financial tool on the AgentPay MCP server.
This record as markdown: /tools/advaitgore-agent-payment/update-mandate.md
What update_mandate does on AgentPay
AI agents use update_mandate to commit financial operations through AgentPay, usually the final step of a payment, billing, or trading workflow. A call moves real money.
Why update_mandate is rated Critical
A mandate on AgentPay defines the rules governing what an AI agent can spend — including spending caps, allowed merchants, and time windows. Updating a mandate could raise spending caps, add new merchants, or extend time windows, directly affecting financial authorization controls.
From the tool's definition Tool name 'update_mandate' on AgentPay server, which manages spending caps, allowed merchants, and time windows for AI agent purchases
Attacks that exploit this kind of access
The rule that runs update_mandate safely
PolicyLayer is an MCP gateway: it sits between your AI agents and AgentPay, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For update_mandate, this is the rule to start with:
Any call to update_mandate is blocked until a human approves it. The rest of the server keeps working.
The button opens the PolicyLayer dashboard: create your workspace, connect AgentPay, apply this rule, and every update_mandate call is checked against it from then on.
Questions about update_mandate
update_mandate is a financial tool on the AgentPay MCP server. It is categorised as a Financial tool in the AgentPay MCP Server, which means it involves financial transactions. Block by default and require explicit approval.
Register the AgentPay MCP server in PolicyLayer and add a rule for update_mandate: 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 AgentPay. Nothing to install.
update_mandate is a Financial 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 update_mandate 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_mandate. 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_mandate is provided by the AgentPay MCP server (advaitgore/agent_payment). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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