"A server for Shopify development tools and API integration" matching MCP servers:

Provides a collection of MCP servers for computational chemistry tasks including molecular generation and retrosynthesis. Also offers property prediction and molecule pricing capabilities.

Enables MCP-capable AI clients to characterize proteins end to end: PDB/mmCIF validation, sequence extraction and typing, pLDDT confidence summaries, metal-site geometry with bidentate chelate detection, GROMACS trajectory metrics and plots, and live UniProt, AlphaFold DB, and RCSB lookups. Also ships a point-and-click Protein Lab web UI (and a persistent run registry) so students and wet-lab biologists can get the same results without any client setup.

Enables AI agents to query Human Phenotype Ontology clinical phenotype terms, navigate term hierarchies, and retrieve gene-disease and disease-phenotype annotations through keyless MCP tools.

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 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.

Enables deep probabilistic analysis of single-cell omics data using scvi-tools through natural language. Supports SCVI for scRNA-seq analysis, SCANVI for cell type annotation, TOTALVI for multi-modal RNA/protein data, and PEAKVI for scATAC-seq analysis.

Enables searching cryo-EM density maps in EMDB and raw datasets in EMPIAR, with filtering by resolution, keyword, and cross-referencing between the two databases.

This server enables multi-agent conversations for interacting with Cirro's biological data platform through its OpenAPI interface, auto-generated using AG2's MCP builder.

A comprehensive Model Context Protocol (MCP) server for accessing the STRING protein interaction database. This server provides powerful tools for protein network analysis, functional enrichment, and comparative genomics through the STRING API.

Enables querying and accessing hivtools data through a REST API and MCP-compatible tools.

Provides access to BioThings.io APIs for comprehensive gene and variant annotations, enabling seamless integration of biological data into workflows.

An MCP server that provides access to the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, offering 30 tools for searching and analyzing biological data like pathways, genes, and compounds. It supports integration with LangChain and Ollama to enable LLMs to interact with comprehensive genomic and chemical datasets.

MCP server for Ketcher chemical structure editor integration, enabling SMILES/MOL/InChI conversion, image generation, molecular property calculation, and validation.

A server providing access to NCBI E-utilities API for searching and retrieving data from databases like PubMed, Protein, and Nucleotide.

Provides access to the ClinicalTrials.gov AACT database, enabling analysis of clinical trial data, tracking development trends, and generating therapeutic landscape insights.

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.