"Information about Microsoft Graph API" matching MCP servers:

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.

Enables LLMs and AI agents to search a biomedical knowledge graph for concepts and study variables, traverse semantic relationships, and look up BioData Catalyst PIC-SURE paths for cohort building.

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.

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.

Enables AI assistants to query genetic variant data, gene constraints, and population genetics information from the gnomAD (Genome Aggregation Database) through its GraphQL API. Supports searching for genes and variants, retrieving constraint scores, analyzing population frequencies, and accessing genomic coverage data.

Agent-callable canine genomics API providing breed-stratified allele frequencies, pathogenicity predictions, and variant-gene-breed-disease knowledge graph for dog DNA.

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 querying of the Monarch Initiative biomedical knowledge graph for genes, diseases, phenotypes, and their associations through natural language or direct tool calls.

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.

A unified biomedical graph database that integrates 50+ primary data sources — genes, proteins, compounds, diseases, pathways, and clinical data — into a single queryable graph with billions of cross-reference edges. Its native MCP server gives LLMs direct access to structured, authoritative biomedical data, complementing their reasoning with reliable identifiers and up-to-date database content.

Enables querying and retrieving cell line records from the Cellosaurus knowledge base via its REST API, including searching, fetching by accession, and accessing release information.

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.

Empowers AI agents with direct access to the official ClinicalTrials.gov database, enabling programmatic searching, retrieval, and analysis of clinical study data through a Model Context Protocol interface.

MCP server that exposes the UniProt REST API to LLM clients, enabling search and retrieval of protein data via tools like search_uniprotkb, get_entry, and map_ids.

Enables editing and querying of Gene Ontology Causal Activity Models (GO-CAMs) through the Barista API. Supports model creation, individual and fact management, evidence addition, and causal pathway construction for biological knowledge representation.

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.