"Finding the best Minecraft plugin compatible with the Cursor tool" matching MCP servers:

Enables LLM-based agents to interact with FHIR healthcare data through natural language prompts, providing full CRUD operations on FHIR resources, document processing, and semantic search capabilities.

Manages blood pressure readings (create, read, update, delete) via an MCP server, integrable with Open WebUI.

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

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 searching the NIAID Data Ecosystem for biomedical research resources including datasets, clinical studies, and publications using Elasticsearch queries.

Explains why two scientific papers disagree. A contradiction explorer for bench scientists that compares two studies' designs and grounds every claim in a verbatim quote from the source text.

An MCP server that grounds protein research in the UniProt SPARQL endpoint, providing tools for querying proteins, sequences, variants, diseases, and more via intent-named tools and raw SPARQL.

An MCP server that lets an LLM answer a pharmacist's question about drug shortages by normalizing drug names, finding pharmacologic alternatives, and checking their shortage status using public FDA and NLM data.

Enables MCP-compatible clients to act as an AI receptionist for a small medical clinic, handling appointment booking and rescheduling, patient registration, intake, reminders, and FAQ answers.

Connects Claude to the U.S. National Library of Medicine MeSH APIs to search and retrieve medical authority data, descriptors, and qualifiers. It enables library and metadata staff to perform subject analysis and confirm terminology within an AI-assisted cataloging workflow.

Enables language models to search biomedical literature, fetch sequences, and follow links across Entrez databases through eleven read-only tools wrapping the nine NCBI Entrez E-utilities. It handles URL building, pacing, redirects, response caps, and API-key redaction so queries can be answered without a browser or scraping.

A structure-aware MCP server for querying the SPOKE biomedical knowledge graph, enabling entity resolution, schema introspection, path finding, and safe Cypher queries for biomedical knowledge inference.

Grounds gene-nomenclature work in the HUGO Gene Nomenclature Committee (HGNC) dataset, enabling resolution of gene symbols and IDs to canonical HGNC identifiers, plus cross-references and batch operations.

An MCP server implementing the ROBINS-I V2 framework for risk-of-bias assessment in non-randomized studies, with deterministic algorithms and full provenance. It enables users to parse study documents, specify target trial results, answer signalling questions with evidence-bound quotes, and compute or override domain judgements.

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

MCP server that provides tools to query harmonized gene-disease validity data from the Gene Curation Coalition, supporting consensus and conflict detection for gene-disease assertions.

Enables querying the Polish National Health Fund (NFZ) public API for medical waiting lists and service dictionary, allowing AI to compare wait times and find providers.

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).

Provides interpretable variant effect predictions for 4.2 million ClinVar variants using the EVEE API. Enables searching, comparing, and analyzing genetic variants with AI-generated mechanistic interpretations and disruption profiles.

Privacy layer for healthcare AI agents. Pseudonymises patient identifiers (NHS numbers, names, dates of birth, addresses; UK and US) into labelled tokens locally before text reaches an agent, then restores the originals afterwards, keeping the token map out of agent context.