"Developing a Flutter application with embedded React Native" matching MCP servers:

Enables AI agents to query free biomedical and pharmaceutical APIs for clinical trials, drug data, molecular structures, adverse events, and research literature.

Enables LLM agents to query de-identified FHIR-shaped hospital data through audited, read-only tools for patients, encounters, conditions, observations, medications, and interaction checks, while any medication write stays a draft that a clinician must confirm out-of-band.

Provides oncology data (research, news, FDA approvals, clinical trials) and IBM MAMMAL biomedical predictions (PPI, DTI, ClinTox) as MCP tools. Allows AI agents to query cancer datasets and run predictions through a remote MCP server.

Enables genomic sequence analysis through the Evo 2 model, supporting DNA sequence scoring, embedding, generation, and variant effect prediction with multiple model checkpoints (7B, 40B, 1B parameters).

Enables variant annotation and effect prediction using the Ensembl VEP API, with support for batch and single queries.

An open source biomedical research agent that provides LLMs with 28 tools for drug discovery, protein analysis, literature search, medical imaging, omics, and sandbox execution, all running locally via Ollama and MedGemma.

An MCP-native agentic copilot for dental practices that orchestrates multiple MCP tools to analyze X-rays, pull patient history, generate drafts, and propose recalls, streaming results live to a React dashboard.

Enables querying Brazilian PCDT clinical protocols from Conitec and generating concise, context-specific treatment summaries using a local LLM, with verified literal citations and links to official PDFs.

Enables querying and monitoring Brazilian Federal Council of Medicine resolutions on AI, telemedicine, and electronic medical records, with a local searchable copy and official document links.

MCP server that reads glucose data from a FreeStyle sensor via the LibreLinkUp API, providing current glucose and history with explicit coverage and gaps.

Enables querying Anvisa's open data for drug registration status and recent medical devices, with heuristic AI-use classification using a locally hosted LLM.

A Model Context Protocol (MCP) server for interacting with Gen3 data commons, with GraphQL query validation to reduce hallucinations.

Enables a dental office's AI agent to verify benefits for a batch of up to 25 patients in a single MCP call, returning coverage percentages, frequency limits, waiting periods and deductible/annual-maximum remaining, each tied to a plan-clause citation. Exceptions such as identity mismatches or ambiguous cases are routed to a human review queue rather than guessed, with every call audit-logged.

Enables agents to interact with a clinic booking API, including listing specialties, doctors, and a patient's appointments, and booking or cancelling appointments when the active profile permits, while preserving the caller's authority and screening tool descriptions for safety.

Exposes a clinic's knowledge base and structured records to Claude Desktop as callable tools, with read tools grounded with citations and write tools gated behind approval.

Enables querying a synthetic patient dataset with tools to look up patients by ID, age, disease, name, and get statistics, connecting Claude Desktop to local data.

Enables LLM clients and agents to produce realistic synthetic medical referral letter PDFs — a German Überweisungsbrief/Arztbrief or the same letter in another language — either from structured JSON with deterministic, seeded rendering or from a free-text description written by a configured LLM. Each call returns the finished PDF as an embedded resource plus the completed letter content and its seed as structured data.

Enables LLM agents to search biomedical literature, retrieve article details, find related papers, manage caching, and download open-access full texts through MCP with structured, agent-friendly responses.

Provides safe read-only access to synthetic healthcare data via FHIR R4, enabling AI assistants to search patients, retrieve vitals, and summarize conditions using a public sandbox.

Identifies plants from photos and determines whether a species is native, introduced, or invasive in a given country, drawing on GBIF, GRIIS, and GISD data, and also provides management recommendations and country alien-species lists.

Enables read-only FHIR access to Practice Fusion EHR to search patients, appointments, conditions, medications, and lab results.

Enables AI coding agents to search and retrieve official CryoSPARC documentation with version awareness, using a local prebuilt index for safe and fast access.

Enables users to search multiple public life-science data repositories (GEO, ENA, CELLxGENE, PRIDE, DataCite) with a single query, returning a unified ranked list of datasets with ontology-expanded terms and per-source error reporting.

Enables querying FDA regulatory metadata for drugs, biologics, and medical devices through the openFDA API, including resolving application numbers and product names to authoritative regulatory details.

Enables AI assistants to securely read a user's own sundhed.dk health record data, including medications, lab results, vaccinations, and referrals, after MitID login via a local browser session.

Enables querying a veterinary clinic's services, summary, and availability from live data.

Enables biopharma catalyst research by aggregating signals from ClinicalTrials.gov, PubMed, SEC EDGAR, openFDA, and Yahoo Finance, with a single tool to audit a ticker/drug combination and return a forensic verdict.

Enables users to perform common laboratory calculations—reconstitution concentration, unit conversion, C1V1 dilution, molarity, percent w/v, and serial dilution—through MCP tools, with input validation and no network calls or stored data.

Enables graph-based fraud propagation scoring for clinical diagnostics, diffusing risk across entities with a deterministic fallback when the ML model is unavailable.

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.