"Resources for Coding in Python" matching MCP servers:

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.

Executes SPARQL queries against biological and biomedical RDF databases from the RDF Portal, with additional REST API integrations for bioinformatics resources.

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.

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.

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.

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 coding agents to interact with the Reactome pathway database, including search, lookup, hierarchy traversal, SBML/SBGN export, and gene-set enrichment analysis.

Provides read-only access to the ProPaths verified protein interactome, letting AI agents search proteins, retrieve mechanistic interaction details, and explore pathway ontology through MCP tools, resources, and prompts.

Renders interactive 2D molecular structure diagrams from SMILES notation and computes molecular properties like molecular weight, LogP, and TPSA, directly in the chat.

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.

An MCP server that enables AI coding assistants to interact with Rosetta, PyRosetta, and Biotite for running RosettaScripts, validating XML, translating between Rosetta and Biotite, scoring structures, and querying documentation.

▎ 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.

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

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.

Enables AI assistants to query the Ubergraph biomedical ontology SPARQL endpoint with tools for custom SPARQL queries, term lookup, search, and hierarchy traversal.

Provides seamless access to the Protein Data Bank in Europe (PDBe) API and search capabilities, enabling AI clients to query protein structures, perform advanced searches, and retrieve structural biology data.

Enables querying genomics data from the Alliance of Genome Resources across model organisms including human, mouse, rat, zebrafish, fly, worm, yeast, and xenopus. Supports gene searches, disease associations, expression data, orthologs, phenotypes, and molecular interactions through natural language.

A comprehensive Model Context Protocol (MCP) server that provides access to the AlphaFold Protein Structure Database through a rich set of tools and resources for protein structure prediction analysis.