"Examples of complex problem-solving using multiple tools" matching MCP servers:

Enables searching a manually curated database of stable macromolecular protein complexes by protein or complex name, gene, GO term, or biological process, and fetching individual records by accession to retrieve subunits with UniProt identifiers, biological roles, and stoichiometry. Complements UniProt, IntAct, and STRING, and can be used keyless over a hosted gateway endpoint or run locally over stdio.

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

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

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

A Model Context Protocol (MCP) server that provides access to the Protein Data Bank (PDB) - the worldwide repository of information about the 3D structures of proteins, nucleic acids, and complex assemblies.

Provides comprehensive access to the UCSC Genome Browser API, enabling queries of genomic data, DNA sequences, gene annotations, variants, and metadata across multiple species and assemblies.

Enables protein structure and sequence searches using FoldSeek, with support for multiple databases, automatic model downloads, and structured job management.

Enables complex searches, sequence mapping, genomic analysis, and metadata retrieval for non-coding RNA sequences from the RNAcentral database.

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 functional enrichment analysis of gene lists against multiple pathway and ontology databases, plus gene/protein identifier conversion and cross-species ortholog mapping.

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.

Validates the physical and chemical plausibility of ligand–protein docking poses using the PoseBusters tool.

MCP server for biological protein design, folding, and affinity prediction using Refua tools, with optional support for ADMET, clinical simulation, preclinical planning, wet-lab automation, and more.

Enables querying relationships between plant species, small molecules, and mitochondrial Complex I inhibitors by bridging natural-product, biodiversity, and PubMed datasets. Allows LLMs to perform structured searches and reasoning over biological data to identify potential plant-derived mitochondrial inhibitors.

Enables keyless lookup of marine species and genus names, retrieval of full taxonomic lineages by AphiaID, and common vernacular names across languages via MCP tools.

Reproduces the in-silico toxicological profile of Heracleum sosnowskyi metabolites from Rassabina & Fedorov (2025) using open-source models for LD50 prediction, toxicity classification, chemical space clustering, and synthesis cost estimation.