"How to execute commands using a command line interface" matching MCP servers:

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.

Provides an MCP interface to the ROBOT command-line tool for OWL ontology editing, enabling operations like merging, reasoning, and conversion via natural language.

A framework that integrates Brain-Computer Interface technology with the Model Context Protocol to enable real-time neural signal processing and AI-powered interactions for healthcare, accessibility, and research applications.

Provides a programmatic interface to the Genome Aggregation Database (gnomAD) API across versions v2.1.1, v3.1.2, and v4.1.0. It enables users to query gene metadata, variant information, population frequencies, and ClinVar data through a unified schema.

Provides comprehensive BioPython capabilities for biological sequence analysis, alignment, database access (GenBank, UniProt, PubMed), protein structure analysis, and phylogenetics through a Model Context Protocol interface for AI-assisted bioinformatics workflows.

Provides seamless access to UniProtKB protein data, enabling querying of protein entries, sequences, Gene Ontology annotations, and ID mappings through a typed, resilient interface.

Enables AI agents to search, filter, download files, and generate reports from the IGVF Data Portal using natural language commands.

MCP server for interacting with Galaxy bioinformatics platform, enabling AI assistants to connect to Galaxy instances, search and execute tools, manage workflows, and access other features.

Exposes pipen bioinformatics pipelines as MCP tools, allowing AI assistants to discover and run complex workflows through a progressive disclosure interface.

Provides a natural language interface for scRNA-Seq analysis using the Scanpy library, supporting operations such as data preprocessing, clustering, and visualization. It enables AI agents and clients to perform complex single-cell transcriptomics workflows through the Model Context Protocol.

Enables LLM agents to design proteins, predict structures, score interfaces, and run molecular dynamics simulations through a unified interface.

🔍 Enable AI assistants to search, access, and analyze PubMed articles through a simple MCP interface.

Connects PyMOL to Claude AI through the Model Context Protocol, allowing for conversational structural biology and molecular visualization through natural language commands.

🔍 A biomedical literature annotation and relationship mining server based on PubTator3, providing convenient access through the MCP interface.

A Model Context Protocol server that enables AI assistants to interact with LAMMPS for molecular dynamics simulations through natural language commands.

A specialized MCP server for Metal-Organic Framework research that provides tools for database searching, structural optimization, and energy calculations via ASE. It enables scientific workflows by allowing users to interact with MOF data and perform chemical simulations through a standard SSE interface.

Enables natural language interface for single-cell RNA-Seq analysis using Liana. Supports reading/writing scRNA-Seq data, cell-cell communication analysis, and visualization through circle plots and dotplots.

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.

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