Query the FDA drug enforcement (recall) database. Returns recall classification (Class I/II/III), reason, distribution, product description, and voluntary/mandatory flag. License: openFDA CC0 1.0; commercial redistribution permitted.
AI agents call query_fda_drug_recalls to retrieve information from TensorFeed without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
skip | number | — | Pagination offset (0-25000) |
sort | string | — | Sort by field (e.g. report_date:desc) |
limit | number | — | Max records to return (1-100) |
search | string | — | openFDA Lucene-style search expression. Examples: classification:"Class+I", reason_for_recall:contamination |
Parameters from the server's own tool schema.
This tool retrieves and queries public FDA drug recall information without side effects. It is purely informational—reading from an external database. The openFDA CC0 license and emphasis on 'returns' data confirm it is a read-only operation. Low severity because misuse would only result in information disclosure, not data modification, code execution, or financial impact.
From the tool's definition Tool name contains 'query' and description states it 'Returns' data from FDA database (recall classification, reason, distribution, product description). No language indicating creation, modification, deletion, or execution of external operations.
Attacks that exploit this kind of access
Query the FDA drug enforcement (recall) database. Returns recall classification (Class I/II/III), reason, distribution, product description, and voluntary/mandatory flag. License: openFDA CC0 1.0; commercial redistribution permitted. It is categorised as a Read tool in the TensorFeed MCP Server, which means it retrieves data without modifying state.
query_fda_drug_recalls accepts 4 parameters: skip, sort, limit, search. The full parameter table on this page comes from the server's own tool schema.
Register the TensorFeed MCP server in PolicyLayer and add a rule for query_fda_drug_recalls: 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.
query_fda_drug_recalls 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 query_fda_drug_recalls 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 query_fda_drug_recalls. 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.
query_fda_drug_recalls 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.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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