Check whether a domain is AFTA-certified (Agent Fair-Trade Agreement). AFTA is an open standard: cryptographically-signed receipts, transparent pricing, no-charge guarantees for failed responses, on-chain settlement, and federated trust between participating sites. The check runs 6 deterministic ...
Part of the TensorFeed server.
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AI agents call check_afta_certification to retrieve information from TensorFeed 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 check_afta_certification 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": {
"check_afta_certification": {}
}
}See the full TensorFeed policy for all 79 tools.
These attack patterns abuse exactly the kind of access check_afta_certification 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.
Check whether a domain is AFTA-certified (Agent Fair-Trade Agreement). AFTA is an open standard: cryptographically-signed receipts, transparent pricing, no-charge guarantees for failed responses, on-chain settlement, and federated trust between participating sites. The check runs 6 deterministic probes against the target domain (e.g. tensorfeed.ai, terminalfeed.io): well-known endpoint, receipts endpoint, x402 payment manifest, pricing transparency, free trial availability, federation membership. Returns score, verdict, and which checks passed/failed.. It is categorised as a Read tool in the TensorFeed MCP Server, which means it retrieves data without modifying state.
Register the TensorFeed MCP server in PolicyLayer and add a rule for check_afta_certification: 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 TensorFeed. Nothing to install.
check_afta_certification 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 check_afta_certification 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 check_afta_certification. 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.
check_afta_certification is provided by the TensorFeed MCP server (https://mcp.tensorfeed.ai/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 79 TensorFeed tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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