"Information about Angular framework or concept" matching MCP servers:

Enables AI-powered genomic variant analysis including variant impact prediction, regulatory element discovery, and batch variant scoring. Currently operates in mock mode as a proof-of-concept awaiting the public release of Google DeepMind's AlphaGenome API.

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.

Allows to retrieve information about an AnnData object via MCP using the read_lazy function from anndata.

Official public, read-only Helena Bioinformatics MCP for source-cited answers about the company and its published products.

Enables querying the gnomAD genome aggregation database for variant, gene, and region information.

Enables AI agents to resolve marine species names to OBIS taxon records, retrieve georeferenced ocean occurrence records with optional date filtering, and pull aggregate statistics such as record counts, contributing datasets, and observed year ranges. Queries the Ocean Biodiversity Information System keylessly over the Pipeworx gateway or as a local stdio server.

Enables querying NCBI genome assemblies, gene details with cross-references, and taxonomy trees with per-node assembly and gene counts, providing structured answers about genomes, genes, and taxonomy.

Enables querying metadata from MyVariant.info, a comprehensive variant annotation database, providing dataset statistics, source information, and build versions.

An MCP server that enables language models to fetch protein information from the UniProt database, including protein details, sequences, functions, and structures.

Provides a natural language interface for single-cell RNA-Seq analysis using the decoupleR framework. It enables users to perform biological pathway inference, data clustering, and visualization through MCP-compatible AI clients.

Enables LLMs and AI agents to query a biomedical knowledge graph stored in RedisGraph, with tools for concept search, synonym enrichment, and study variable discovery through semantic relationships.

Provides a natural language interface for inferring Copy Number Variations (CNVs) from scRNA-Seq data using the infercnvpy framework. It enables users to perform data preprocessing, CNV inference, and visualization through chromosome heatmaps, UMAP, and t-SNE plots.

Framework for building bioengineering automation tools that AI assistants can call via the Model Context Protocol, handling server registration and tool discovery automatically.

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.

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 AI agents to retrieve cited pharmacogenomic and gene-variant information, including drug–gene guidance from CPIC/DPWG and rsID lookups, so responses can quote curated sources instead of relying on memory. A local package also lets users read raw DNA files on their own computer without sending the file data to the remote service.

Enables MCP clients to annotate and classify single human genetic variants in any notation, returning an auditable points-based ACMG verdict with its criteria, gnomAD frequencies, in-silico predictors, ClinVar data, and per-transcript consequences. It is read-only, requires no account or API key, and keeps answers compact while linking back to the source.

Enables AI assistants to rapidly gather and synthesize structural, chemical, conservation, and literature data about protein binding pockets for drug-target triage. Useful as a reconnaissance step before computational binder design.

A bridge connecting AI agents to NCBI's PubMed database through the Model Context Protocol, enabling seamless searching, retrieval, and analysis of biomedical literature and data.

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.

Enables querying the WormBase database for C. elegans and nematode genomics data, including gene information, protein sequences, phenotypes, interactions, and expression patterns through natural language.

Enables AI assistants to search and retrieve bacterial strain details, taxonomy, culture media, 16S rRNA sequences, and genome information from the BacDive database through MCP tools.

Enables LLM-powered applications to look up bacterial and archaeal taxonomy, search genomes, browse and navigate the taxonomic tree, and compare genomes or find phylogenetic paths between taxa. It works out of the box with a built-in reference dataset covering major phyla and can be pointed at full Genome Taxonomy Database TSV files for comprehensive queries.

Enables AI assistants to submit genomic sequences or NCBI accessions to antiSMASH for secondary metabolite biosynthetic gene cluster analysis, check job status, retrieve and download results, and query server status across bacteria, fungi, and plant servers.

Enables users to search rRNA sequences by organism, accession, or taxonomy, retrieve detailed sequence metadata, evaluate probes and primer pairs, and list available databases and taxonomies through MCP tools.

Enables AI-driven pharmacogenomic analysis by querying structured genetic variant, drug response, and disease risk data. Supports natural language questions about medications, traits, and health risks based on user genome data, with privacy-first local execution.

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 interaction with MGnify metagenomics resources and tools through the Model Context Protocol. Provides access to MGnify's API for querying and analyzing metagenomic datasets and related biological information.

Enables AI assistants to search and retrieve prokaryotic names, taxon details, full classifications, and rank-based browsing from the List of Prokaryotic names with Standing in Nomenclature in real time, plus read related information pages.

A framework that integrates Brain-Computer Interface technology with the Model Context Protocol to enable real-time neural signal processing and AI-powered interactions for healthcare, accessibility, and research applications.