Submit an order to ClearSale for fraud analysis. Returns a score (0-100) and a decision (APROVADO / REPROVADO / EM_ANALISE). Include as much signal as possible — billing + shipping, IP, device, items, and payment — to improve the decision.
AI agents invoke send_order_for_analysis to trigger actions in Mcp Ap2. 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.
This tool submits data to an external service (ClearSale) and triggers a fraud analysis process. It is not a simple read (it causes an external action), not purely destructive, and not directly financial (it doesn't move money). It executes an external operation with side effects that depend on the order arguments, making Execute the best fit.
From the tool's definition 'Submit an order to ClearSale for fraud analysis' — triggers an external operation (submission to a third-party fraud analysis service) whose effects depend on the arguments provided
Documented attack patterns abuse exactly the kind of access send_order_for_analysis 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 send_order_for_analysis:
{
"version": "1",
"default": "deny",
"tools": {
"send_order_for_analysis": {
"limits": [
{
"counter": "send_order_for_analysis_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}send_order_for_analysis stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
Free to start. No card required.
Submit an order to ClearSale for fraud analysis. Returns a score (0-100) and a decision (APROVADO / REPROVADO / EM_ANALISE). Include as much signal as possible — billing + shipping, IP, device, items, and payment — to improve the decision. It is categorised as a Execute tool in the Mcp Ap2 MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Mcp Ap2 MCP server in PolicyLayer and add a rule for send_order_for_analysis: 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.
send_order_for_analysis 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 send_order_for_analysis 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 send_order_for_analysis. 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.
send_order_for_analysis 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.
Free to start. No card required.
1300 Mcp Ap2 tools catalogued and risk-classified — across an index of 43,000+ MCP servers.