"AI-Powered Virtual Medical Consultation Assistant" matching MCP servers:

Enables AI-powered medical information retrieval through FHIR clinical document search and GraphRAG-based exploration of medical entities and relationships. Combines vector search with knowledge graph queries for comprehensive healthcare data analysis.

MCP server for evidence-based Chinese legal consultation. It routes labor law questions to a knowledge base and other queries to public search, returning answers with citations and fallback reasons.

Enables chat, document search (RAG), and a declarative SQL tool builder over MCP so any client can use these capabilities.

An MCP server that analyzes patient symptoms using AI, suggests potential diagnoses, and retrieves relevant medical literature from PubMed.

Enables AI assistants to query authoritative medical APIs locally without API keys for drug information, health statistics, medical literature, clinical guidelines, and pediatric sources. Provides resilience features such as circuit breakers, rate limiting, caching, and health checks.

Enables end-to-end testing of voice-enabled web applications by simulating a synthetic user with a virtual microphone, virtual speakers, a real browser, and a viewable display, allowing audio injection, speech capture/transcription, and browser automation.

Enables querying medical documents stored in Qdrant using semantic retrieval, allowing users to search PubMed articles through the Model Context Protocol.

An MCP server that provides AI agents with a persistent, PostgreSQL-backed virtual filesystem, supporting session-isolated file operations, cross-session shared stores, and glob/grep search.

Enables MCP clients such as Claude and Cursor to purchase virtual phone numbers, wait for SMS verification codes, and resend, complete, or cancel activations using the user's API key.

Content writing toolkit for headline generation, readability scoring, tone analysis, outline building, and plagiarism similarity checking.

Enables discovery, retrieval, summarization, comparison, methodology and limitation analysis, research gap identification, and local management of academic papers via arXiv and Gemini AI.

Provides web search and code execution capabilities using OpenAI models, with optional code interpreter and conversation continuity via response IDs.

Enables AI assistants to monitor and analyze industrial process data from DCS/SCADA systems via MCP protocol, with domain expert knowledge for anomaly detection and recommendations.

Enables AI assistants to query authoritative medical sources such as FDA, WHO, PubMed, RxNorm, and ClinicalTrials.gov for drug information, health statistics, medical literature, clinical guidelines, and pediatric resources. Runs locally with no API keys or cloud dependencies, adding resilience, caching, and evidence grading to every lookup.

Enables AI clients to query authoritative medical APIs for drug information, health statistics, literature, clinical guidelines, trials, and pediatric resources locally without API keys. It also provides resilience, caching, health checks, and evidence-grading features for reliable retrieval.

Enables AI clients to query authoritative medical APIs for drug information, health statistics, clinical guidelines, trials, and literature from sources such as FDA, WHO, PubMed, RxNorm, and Google Scholar, running locally without API keys.

Enables AI clients to search authoritative drug, health statistics, medical literature, clinical guideline, clinical trial, and pediatric sources such as FDA, WHO, PubMed, RxNorm, and Google Scholar, with local privacy and no API keys.

Enables AI clients to query authoritative medical sources such as FDA, WHO, PubMed, RxNorm, and ClinicalTrials.gov for drug information, medical literature, health statistics, clinical guidelines, and pediatric resources through local MCP tools.

Enables AI assistants to query authoritative medical sources such as FDA, WHO, PubMed, RxNorm, and ClinicalTrials.gov for drug information, safety data, health statistics, medical literature, clinical guidelines, and pediatric resources. Runs fully locally with no API keys or data leaving the machine, and includes resilience features like rate limiting, circuit breakers, caching, and health checks.

An agentic Retrieval-Augmented Generation (RAG) system that combines a small curated machine learning knowledge base with real-time web search capabilities, powered by the Model Context Protocol (MCP).