Query the FDA food enforcement (recall) database covering food products distributed in the US. Same shape as drug recalls. License: openFDA CC0 1.0; commercial redistribution permitted.
AI agents call query_fda_food_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: reason_for_recall:listeria, classification:"Class+I" |
Parameters from the server's own tool schema.
This tool retrieves public FDA food recall information without creating, modifying, deleting, or executing operations. It is a straightforward database query that poses minimal risk. The public nature of FDA data and the read-only intent of querying a recall database mean misuse would have negligible blast radius—an AI agent could retrieve information but cannot alter records or trigger external consequences.
From the tool's definition Tool name 'query_fda_food_recalls' and description 'Query the FDA food enforcement (recall) database' indicate data retrieval with no modification capability. The term 'Query' and the reference to a read-only database lookup are key indicators.
Attacks that exploit this kind of access
Query the FDA food enforcement (recall) database covering food products distributed in the US. Same shape as drug recalls. 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_food_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_food_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_food_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_food_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_food_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_food_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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