Add a cash transaction to a tracking session
AI agents use add_cash_transaction to commit financial operations through Shopify Graphql — usually the final step of a payment, billing, or trading workflow. A call moves real money.
This tool records/adds a cash transaction, which directly involves financial operations. Misuse could result in incorrect financial records, fraudulent transactions, or accounting discrepancies in a Shopify store's financial tracking session.
From the tool's definition Add a cash transaction to a tracking session
Attacks that exploit this kind of access
Add a cash transaction to a tracking session. It is categorised as a Financial tool in the Shopify Graphql MCP Server, which means it involves financial transactions. Block by default and require explicit approval.
Register the Shopify Graphql MCP server in PolicyLayer and add a rule for add_cash_transaction: 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 Shopify Graphql. Nothing to install.
add_cash_transaction 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 add_cash_transaction 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 add_cash_transaction. 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.
add_cash_transaction is provided by the Shopify Graphql MCP server (uvu-store/shopify-graphql-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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