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GMPSignal Real-Time Intelligence MCP (59 Tools)

GMPSignal Real-Time Intelligence MCP (59 Tools)

Official
by xpayrcom
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JavaScript
Hybrid

fda_recalls_enforcement

Extracts real-time FDA recall and enforcement data for drugs, devices, and food to support compliance monitoring and risk analysis. Returns structured items with configurable result limits.

Instructions

FDA Recalls & Enforcement - Drugs, Devices, Food: Real-time structured data extraction feed for FDA Recalls & Enforcement - Drugs, Devices, Food.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "fda_recalls_enforcement"
  }
}

Input Schema

NameRequiredDescriptionDefault
maxResultsNoMaximum number of structured items to extract.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.3/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden, and it offers only the word 'Real-time' as behavioral context. It says nothing about whether the call is read-only, whether results are paged or capped, what freshness guarantees mean, or what a 'structured item' contains — all essential for a data-feed tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The text is short, but the space is spent redundantly repeating the name/title rather than front-loading useful information. Nothing is verbose, yet little of the sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a data-extraction feed with no output schema, the description should explain what records are returned (recall class, product, firm, date, enforcement report fields) and any freshness or pagination behavior. None of that is present, leaving the agent unable to predict results beyond the domain.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There is a single parameter with 100% schema description coverage ('Maximum number of structured items to extract'), so the schema already documents it fully. The description adds no extra meaning about what constitutes an 'item' or how maxResults interacts with the feed, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description repeats the tool name and title almost verbatim ('FDA Recalls & Enforcement - Drugs, Devices, Food') and appends the generic phrase 'Real-time structured data extraction feed'. It does convey the domain scope (drugs, devices, food), which is mildly useful, but there is no action verb such as list/fetch/search and no distinction from siblings like global_product_recalls or fda_warning_letters_scraper.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No when-to-use guidance is present at all: no indication of what query context this feed suits, no exclusions, and no mention of how it differs from the other recall- or FDA-related siblings. The agent must infer usage entirely from the name.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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