"Buy Me A Coffee" matching MCP servers:

A unified MCP server for biomedical research that connects AI systems to resources like Ensembl, EuropePMC, STRING, and more, enabling retrieval of verified domain-specific information.

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.

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).

MCP server and Claude Plugin for a full ENCODE Project genomic data and analysis toolkit — search, download, track, and analyze functional genomics experiments

Provides direct SQL access to a locally hosted Reactome database, enabling schema discovery, guarded read-only queries, and ergonomic helpers over the full relational schema.

A Model Context Protocol (MCP) server for interacting with Gen3 data commons, with GraphQL query validation to reduce hallucinations.

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 for searching and accessing RNA sequencing datasets from the European Nucleotide Archive (ENA), supporting bulk, single-cell, and spatial transcriptomics with advanced filtering and download capabilities.

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.

▎ Provides 32 tools for plant-genomics locus lookup across 11 free public backends (Ensembl Plants, Phytozome, UniProtKB, Europe PMC, QuickGO, NCBI BLAST, Gramene, KEGG, STRING-DB, ATTED-II, BAR). Takes a TAIR-style locus plus optional organism and returns gene metadata, functional/pathway annotation, interactions, co-expression, and literature — in single-locus, batch, and cross-source synthesis.

Integrates AlphaFold DB and eight other biomedical data sources into MCP tools for variant clinical reporting, disease-target analysis, structural intelligence, and drug repurposing, with results persisted to a local SQLite knowledge graph.

Enables agents to search a public PubMed-derived corpus by natural language or identifiers and to retrieve publication details while traversing bounded citation and semantic literature graphs.

An MCP server that provides standardized access to biomedical knowledge bases and resources, enabling AI systems to retrieve verified information from sources like bioRxiv, EuropePMC, and various protein/gene databases.

Provides a Model Context Protocol server for accessing and querying biomedical data from BioThings services, including gene, variant, chemical, and taxon annotations.

Provides access to EMBL-EBI bioinformatics data including InterPro domains, Pfam families, protein features, and taxonomy through a unified tool.

A stateless, deterministic Bio-Robotics Core Engine converting biological data (UniProt API) to G-code.

Enables variant annotation and effect prediction using the Ensembl VEP API, with support for batch and single queries.

A Model Context Protocol server providing LLMs with access to the Ensembl genomics database, enabling AI assistants to query gene information, sequences, variants, and other genomic data across multiple species.

Enables AI agents to conversationally interact with genomics research networks for data analysis and discovery across multiple Omics AI Explorer platforms. It provides tools for exploring data collections, examining table schemas, and executing SQL queries against datasets like Viral AI and Neuroscience AI.