"Setting up Minecraft (MCP) servers with Python and Visual Studio Code" matching MCP servers:

An MCP server for querying the KEGG bioinformatics database, providing tools, resource templates, and guided prompts for pathways, genes, compounds, and more.

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.

Enables bioinformatics analysis through natural language conversations with Claude Desktop, automatically generating and executing Python scripts to produce HTML reports and visualizations.

An MCP server for running local LLMs using llama-cpp-python, with built-in tools for generating drug-like molecule SMILES.

Enables AI agents to read and manipulate networks, tables, visual styles, and more in a live Cytoscape Web session through natural language, by connecting over Chrome DevTools Protocol.

Enables users to look up yeast genes/loci, search genes and alleles by free text, and retrieve Gene Ontology annotations from the Saccharomyces Genome Database.

Enables looking up genes, fetching sequences, predicting variant consequences, finding orthologs, and cross-database xrefs via Ensembl REST API through MCP.

Enables AI agents to look up molecular interactions from the EBI IntAct database by gene/protein name or UniProt ID, returning detection method, interaction type, organism, PubMed reference, and MI confidence score, along with fast interaction counts. It is keyless and available either through a hosted MCP endpoint, a plain HTTP API, or a local stdio server.

Look up variant allele frequencies by ancestry, gene loss-of-function constraint, gene variant lists, and sequencing coverage over gnomAD — with ClinVar significance joined in — via MCP.

Enables AI agents to look up approved human genes by official symbol, fuzzy-search symbols, names and aliases, and reverse-map external database identifiers (Entrez, Ensembl, UniProt, OMIM, RefSeq, UCSC) back to canonical gene records with full annotations and cross-references.

Enables AI agents to resolve scientific (Latin binomial) names to Open Tree of Life taxon IDs, retrieve full taxonomic details, synonyms, and ancestor lineages, and find the most recent common ancestor of up to 10 taxa within the synthetic tree of life. Runs keylessly over a hosted gateway endpoint or locally via npx.

A unified biomedical graph database that integrates 50+ primary data sources — genes, proteins, compounds, diseases, pathways, and clinical data — into a single queryable graph with billions of cross-reference edges. Its native MCP server gives LLMs direct access to structured, authoritative biomedical data, complementing their reasoning with reliable identifiers and up-to-date database content.

Enables LLMs and AI agents to search a biomedical knowledge graph for concepts and study variables, traverse semantic relationships, and look up BioData Catalyst PIC-SURE paths for cohort building.

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.

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.

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.

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 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 DNA sequence analysis and variant effect prediction using Evo2-7B via MCP tools, providing forward inference, likelihood scoring, and batch variant comparison through natural language.