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"Understanding and Using JSON" matching MCP servers:

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    Condition-aware ingredient & product safety intelligence for AI agents. Every answer carries a claim-level evidence attestation, verdict, an evidence tier, and a citation – curated against authoritative sources (LactMed, InfantRisk, PubMed, DSLD, DermNet, EU CosIng) by Health AI. Hosted MCP server – no install, no key. Endpoint: https://mcp.healthai.com (Streamable HTTP, JSON-RPC 2
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    MIT
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    Provides live US healthcare cost data including procedure cost estimates, provider pricing, insurance coverage rules, and medical bill analysis using real hospital transparency and CMS data.
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    MIT
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    Enables conversational access to 400,000+ clinical trials on ClinicalTrials.gov, allowing users to search, compare, and retrieve trial details using plain English through MCP-compatible clients like Cursor and Claude Desktop.
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    MIT
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    Enables searching and retrieving detailed information from PubMed articles using the NCBI Entrez API. Supports configurable search parameters including title/abstract filtering and keyword expansion to find relevant scientific publications.
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    A TypeScript MCP server for interacting with CDISC Define-XML 2.0 and 2.1 files, enabling users to load, search, and retrieve clinical data metadata including datasets, variables, and codelists. It supports local file processing with document caching and provides responses in both JSON and Markdown formats.
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    A reference MCP server for clinic scheduling and intake, demonstrating production patterns like tenant isolation, idempotent writes, and structured errors using synthetic data.
    5
    MIT
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    An MCP server that provides a toolbox for interacting with EPA SWMM stormwater models, enabling users to analyze model data and interpret results through LLM-driven tools. It assists stormwater modelers in understanding hydraulic systems and modeling behavior using natural language interfaces.
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    MIT
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    Enables querying US regulated-care providers (GLP-1 clinics) with tools for searching, retrieving details, and checking compliance, using natural language or function calls.
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    MIT