"An introduction to GraphQL or resources for learning GraphQL" matching MCP servers:

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.

MCP server exposing REINVENT4 generative molecular-design operations as validated, LLM-callable tools for drug discovery, including sampling, transfer learning, reinforcement learning, and molecular analysis.

A Model Context Protocol (MCP) server for interacting with Gen3 data commons, with GraphQL query validation to reduce hallucinations.

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 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 reproducible target-disease evidence dossier assembly and validation by replaying frozen Open Targets GraphQL responses and checking citations and structured assertions against deterministic scientific contracts.

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.

Enables AI agents to search public cancer genomics studies (TCGA, CPTAC, MSK, and more), fetch full details for individual studies, resolve gene symbols to Entrez ids, and list cancer types. Works keylessly against open cBioPortal data over a hosted MCP endpoint, a local stdio server, or plain HTTP.

An MCP server providing public plant bioinformatics APIs including UniProt, NCBI, InterProScan, PDB, AlphaFold, Ensembl Plants, and web-based resources like Sol Genomics and BAR, without local data. It supports gene lookups, protein summaries, structure retrieval, and functional annotations through natural language.

Enables quantum machine learning operations using Qiskit, including executing quantum circuits, computing quantum kernels, training variational quantum classifiers, and evaluating quantum ML models.

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.

An MCP server for MARRVEL that enables AI agents to access genetics databases and variant analysis tools for rare disease research.

Enables RNA structure analysis, sequence evaluation, and inverse design using geometric deep learning models. Supports both quick computational analysis and long-running batch processing for generating RNA sequences that fold into target structures.

Enables protein stability prediction ($DeltaDelta$G and $Delta$Tm) and systematic mutation analysis using the SPIRED-Stab deep learning model. It supports single variant analysis, batch processing, and job monitoring via Docker-based inference.

Enables prediction of blood-brain barrier permeability for drug molecules via machine learning, with molecule name lookup, plain-language explanations, similar drug search, and applicability domain checks. Exposes these as MCP tools and orchestrates them via a LangGraph agent.

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.

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.

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 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.