"How to use or perform actions in Apple Calendar" matching MCP servers:

Provides seamless access to the Protein Data Bank in Europe (PDBe) API and search capabilities, enabling AI clients to query protein structures, perform advanced searches, and retrieve structural biology data.

Enables AI assistants to perform NCBI BLAST sequence similarity searches through natural language, supporting nucleotide and protein searches, custom database creation, and multiple output formats.

MCP server that exposes STRING database functionality, allowing AI agents to resolve protein identifiers, retrieve interaction networks, perform homology lookups, and run functional enrichment analysis.

An MCP server for the gget bioinformatics library that enables AI assistants to perform complex genomics queries, including gene sequence retrieval, BLAST alignments, and protein structure predictions.

Enables AI assistants to perform genomic variant analysis using OakVar, including running annotation pipelines, managing 200+ annotator modules, querying variant databases, and generating reports in various formats.

MCP server for RNA-seq downstream analysis, wrapping R scripts to generate plots and perform analyses like PCA, volcano, heatmap, enrichment, and WGCNA.

Provides a natural language interface for single-cell RNA-Seq analysis using the decoupleR framework. It enables users to perform biological pathway inference, data clustering, and visualization through MCP-compatible AI clients.

Enables LLM agents to perform stateful genome-scale metabolic modeling with COBRApy through the Model Context Protocol, including loading models, knocking out genes, running flux balance analysis, and inspecting flux distributions.

BioOpenMCP enables users to run bioinformatics tools like FastQC, Cutadapt, and STAR with background execution and status checking. It integrates with Claude Desktop to perform quality control, trimming, alignment, and reporting via natural language.

Control PyMOL from Cursor via natural language. Enables describing molecular structures and styles in plain language to execute PyMOL commands through XML-RPC.

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.

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.

Enables AI assistants to clean PDB structures and run initial-stage energy relaxation for biomolecular modeling. It provides a structured workflow for preparing structures before production molecular dynamics or coarse-graining pipelines.

Renders interactive 2D molecular structure diagrams from SMILES notation and computes molecular properties like molecular weight, LogP, and TPSA, directly in the chat.

Enables analysis of bulk RNA-seq data using natural language queries, executing R and Python in a Docker container with automatic sample anonymization and privacy controls.

A Model Context Protocol server that interfaces with Biomart databases, allowing models to discover biological datasets, explore attributes/filters, retrieve biological data, and translate between different biological identifiers.

An MCP server that interfaces with Gigwa for genotyping data import, analysis, and audit, enabling users to perform complex workflows through natural language commands.

MCP server that provides tools for querying the Human Phenotype Ontology (HPO) including term lookup, hierarchy exploration, cross-ontology mappings, and gene-phenotype-disease associations, all grounded in a local SQLite database for fast offline lookups.

A bridge connecting AI agents to NCBI's PubMed database through the Model Context Protocol, enabling seamless searching, retrieval, and analysis of biomedical literature and 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.