Fetch a payment consent and its current authorization status. Iniciador endpoint: GET /consents/{id}.
AI agents call get_consent to retrieve information from Mcp Afip without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves payment consent data and authorization status without creating, modifying, deleting, or executing any operations. Even though it relates to AFIP (Argentine tax authority) and financial systems, the tool itself only reads consent records and does not move money, create financial obligations, or perform destructive actions. The GET method and 'Fetch' verb confirm read-only behavior.
From the tool's definition Tool description explicitly states 'Fetch' and uses GET HTTP method, indicating a read-only query operation without side effects. The endpoint pattern GET /consents/{id} is a standard RESTful read operation.
Documented attack patterns abuse exactly the kind of access get_consent gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Mcp Afip, and nothing reaches the server without passing your rules. This is the rule we recommend for get_consent:
{
"version": "1",
"default": "deny",
"tools": {
"get_consent": {}
}
} get_consent is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Fetch a payment consent and its current authorization status. Iniciador endpoint: GET /consents/{id}. It is categorised as a Read tool in the Mcp Afip MCP Server, which means it retrieves data without modifying state.
Register the Mcp Afip MCP server in PolicyLayer and add a rule for get_consent: 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 Afip. Nothing to install.
get_consent 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 get_consent 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 get_consent. 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.
get_consent is provided by the Mcp Afip MCP server (codespar/mcp-dev-latam). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Mcp Afip, 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 Afip tools catalogued and risk-classified — across an index of 43,000+ MCP servers.