Retrieve a checkout by id.
AI agents call retrieve_checkout to retrieve information from Mcp Ap2 without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool queries and returns checkout information based on an identifier. While it operates within a financial payment system (AP2), the tool itself only reads/retrieves existing data without executing transactions, modifying state, or committing financial obligations. The retrieval of checkout details is a standard Read operation with minimal risk if accessed by an unauthorized agent.
From the tool's definition Tool name 'retrieve_checkout' and description 'Retrieve a checkout by id' indicate data retrieval with no modification or execution of payment operations.
Documented attack patterns abuse exactly the kind of access retrieve_checkout gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Mcp Ap2, and nothing reaches the server without passing your rules. This is the rule we recommend for retrieve_checkout:
{
"version": "1",
"default": "deny",
"tools": {
"retrieve_checkout": {}
}
}retrieve_checkout is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Retrieve a checkout by id. It is categorised as a Read tool in the Mcp Ap2 MCP Server, which means it retrieves data without modifying state.
Register the Mcp Ap2 MCP server in PolicyLayer and add a rule for retrieve_checkout: 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 Mcp Ap2. Nothing to install.
retrieve_checkout is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the retrieve_checkout 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 retrieve_checkout. 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.
retrieve_checkout is provided by the Mcp Ap2 MCP server (@codespar/mcp-ap2). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Mcp Ap2, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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1300 Mcp Ap2 tools catalogued and risk-classified — across an index of 43,000+ MCP servers.