mcp-openfda
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Alternatives to mcp-openfda
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Related Servers
- AlicenseAqualityDmaintenanceEnables querying FDA drug label information including adverse reactions, warnings, and indications via natural language.56 npm1GPL 3.0
- AlicenseAqualityDmaintenanceEnables LLMs to search FDA drug labels and adverse event data via the OpenFDA API, supporting natural language queries for drug safety information.2MIT
- AlicenseBqualityDmaintenanceProvides access to the official FDA DailyMed database for comprehensive drug information, including drug labels, NDC codes, RxNorm mappings, pharmacologic classifications, and FDA application numbers through natural language queries.283MIT
- AlicenseNot gradedqualityBmaintenanceEnables querying FDA medical device regulatory databases including 510(k) clearances, PMA approvals, recalls, and adverse events through natural language.5 npmMIT
- FlicenseNot gradedqualityDmaintenanceEnables AI agents to query and analyze FDA adverse events, drug labels, medical device clearances, and other public health datasets through natural language commands.14-
- FlicenseNot gradedqualityDmaintenanceEnables querying FDA drug approvals, device clearances (510(k)), recalls, and adverse events via the openFDA API, providing tools for clinical and pharmaceutical research.1-
TDQS
Scored across 5 tools
Most tools have clear, distinct purposes: get_drug_adverse_reactions, get_drug_warnings, and get_drug_indications target specific label sections, while search_drug_labels provides broad search. However, search_drug_labels overlaps with the section-specific tools, and ae_pipeline_rag also covers drug label data, creating minor ambiguity.
Three tools follow a consistent get_drug_<section> pattern (get_drug_adverse_reactions, get_drug_warnings, get_drug_indications), but search_drug_labels and ae_pipeline_rag deviate from this pattern. The convention is mostly consistent, with two outliers.
Five tools is well-scoped for a focused FDA drug label API server. Each tool serves a clear purpose without unnecessary bloat, making the count appropriate.
The set covers common drug label sections (indications, warnings, adverse reactions) and provides search and RAG capabilities, but omits other important sections like contraindications, dosage, or interactions. There's no direct tool for retrieving the full label, which is a notable gap.