Screen an entity against Anti-Money Laundering (AML) watchlists including OFAC SDN and UN sanctions. Returns risk level, risk score, recommendation (approve/review/reject), and sanctions match details. Uses Jaro-Winkler fuzzy name matching for accurate detection. Cost: $0.05 USDC per screening. C...
Part of the AgentEconomy Compliance API server.
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AI agents call aml_screen to retrieve information from AgentEconomy Compliance API without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.
Even though aml_screen only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.
Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.
{
"version": "1",
"default": "deny",
"tools": {
"aml_screen": {}
}
}See the full AgentEconomy Compliance API policy for all 3 tools.
These attack patterns abuse exactly the kind of access aml_screen gives an agent. Each links to the full case and the policy that stops it:
Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.
Screen an entity against Anti-Money Laundering (AML) watchlists including OFAC SDN and UN sanctions. Returns risk level, risk score, recommendation (approve/review/reject), and sanctions match details. Uses Jaro-Winkler fuzzy name matching for accurate detection. Cost: $0.05 USDC per screening. Caller must supply a signed X-PAYMENT header on the MCP HTTP request.. It is categorised as a Read tool in the AgentEconomy Compliance API MCP Server, which means it retrieves data without modifying state.
Register the AgentEconomy Compliance API MCP server in PolicyLayer and add a rule for aml_screen: 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 AgentEconomy Compliance API. Nothing to install.
aml_screen 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 aml_screen 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 aml_screen. 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.
aml_screen is provided by the AgentEconomy Compliance API MCP server (https://api.netbrainis.co.za/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 3 AgentEconomy Compliance API tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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