"How to Assess the Security of a Python Application" matching MCP servers:

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.

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).

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

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

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.

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.

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.

An embedded MCP server for Cytoscape Desktop that lets AI agents load networks, set active views, and control the desktop application over HTTP.

MCP server for querying the GWAS Catalog (EBI/NHGRI), a curated catalog of genome-wide association studies. It enables AI agents to search and retrieve study data via natural language or direct tool calls.

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

A Model Context Protocol server providing programmatic access to 3D protein structural data from RCSB PDB, PDBe, and UniProt, enabling search, retrieval, comparison, and analysis of protein structures.

Enables AI agents to browse the Gene Ontology through the EBI QuickGO API, including keyword search for GO terms, retrieval of a term's name, aspect, definition and synonyms by id, and listing the GO annotations tied to a UniProt accession. Runs keyless over HTTP or as a local stdio server, with an optional gateway route that lets plain-English questions be answered without choosing tools manually.

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

Resolves free-text condition and disease strings — trial-registry condition fields, drug-label indications, hand-typed wording — onto the Mondo Disease Ontology, returning the best term id and label along with a trustworthy match-quality label (exact label/synonym, broader, narrower, fuzzy, or no-match) plus cross-ontology xrefs. Optionally expands a resolved term to all of its descendant ids for building subtype-inclusive registry filters.

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.

Enables AI agents to query the WikiPathways open community pathway database via natural language, part of the Pipeworx MCP gateway.

Enables querying the EBI Expression Atlas for gene expression data across species and conditions. Part of the Pipeworx gateway, it provides access to baseline and differential expression studies.

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

Enables querying the CIViC database for clinical interpretations of cancer variants through tools like get_variant_evidence and get_variant_assertions.