"Developing a FHIR-Based Digital Health Application with EHR, PHR, and Phenotyping Frameworks" matching MCP servers:

MCP server that helps AI agents inspect Minecraft project evidence (crash logs, mod files, datapacks) before writing development code.

Enables read-only SMART on FHIR R4 discovery, search, and read operations against public synthetic sandboxes, returning actual empty results and 404s rather than inventing patient data.

Exposes digital twin device data capabilities as MCP tools, allowing MCP clients to query device status, read real-time metrics, fetch time-series data, and check alerts. Includes a simulated PLC driver with a clean interface for connecting real devices via OPC-UA, Modbus, or gateway APIs.

Enables AI assistants to query your local browsing history using keyword search, RAG Q&A, and activity stats.

A privacy-first MCP server for locally managing job, fellowship, and graduate-school applications. It offers tools for tracking application status, analyzing role fit, generating LaTeX CV/cover letters, interview prep, and discovering public jobs from ATS APIs.

Enables an AI to build, inspect, test, and render logic circuits as .dig files, then open them in the Digital app.

A local-first, open-source MCP server that analyzes jobs, matches your CV, tailors documents, and tracks applications — all on your machine with no data uploaded.

Enables AI assistants to query, filter, and update job application records, and to analyze skill demand across postings.

Enables AI harnesses to maintain a persistent memory layer backed by a local SQLite file, providing MCP tools to add, search, deprecate, and synchronize facts without deleting history.

Enables users to store and query their own medical data—labs, medications, diagnoses, wearables, and food logs—in a local Postgres database and interact with it through any MCP client, with deterministic safety checks.

A Claude-compatible MCP server that exposes health-domain tools over 100% synthetic data, built with security and compliance in mind.

Enables agents to locally analyze Huawei Health export data, retrieve activity summaries, tracks, samples, and health context, and generate structured report evidence with optional environmental data.

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

An MCP server that performs comprehensive health checks on project dependencies for JavaScript and Python projects, detecting outdated packages and fetching changelogs.

Lets Claude Code, Codex, and other AI assistants query locally collected Apple Health data, build weekly reports, check sync status, and log workouts or meals by hand.

Implements a secure MCP server with API Key and JWT authentication, providing tools like echo, login, secure_action, and admin_action. Includes MCP Inspector integration for testing and debugging.

This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for FHIR (beta): https://www.cdata.com/download/download.aspx?sku=KIZK-V&type=beta

Privacy-first, read-only repo intelligence for AI coding agents: scans local codebases and recommends MCP servers, repos, and research without sending data to the cloud.

MCP server that lets a hosted LLM securely read a local family health archive and deposit structured reports into an inbox, with a read-biased tool surface and strict path/token enforcement.

Enables scanning projects for dependency vulnerabilities, secrets, license conflicts, code quality, and git health, returning a 0-100 health score with actionable suggestions.