"A platform for discussions, communities, and information sharing - Reddit" 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.

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).

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

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 server that enables AI assistants to interact with cancer genomics data from cBioPortal, allowing users to explore cancer studies, access genomic data, and retrieve mutations and clinical information.

Enables searching ENA's public sequencing data by organism, study, platform, country or date, retrieving FASTQ/BAM download URLs and checksums, and discovering available result types and fields.

MCP server for interacting with Galaxy bioinformatics platform, enabling AI assistants to connect to Galaxy instances, search and execute tools, manage workflows, and access other features.

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 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 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 advanced integrated MCP server platform that combines 600+ tools and multiple biomedical databases to enable comprehensive information retrieval across molecules, proteins, genes, and diseases for accelerating therapeutic research.

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.

MCP server that provides tools to query harmonized gene-disease validity data from the Gene Curation Coalition, supporting consensus and conflict detection for gene-disease assertions.

Enables DNA sequence analysis and variant effect prediction using Evo2-7B via MCP tools, providing forward inference, likelihood scoring, and batch variant comparison through natural language.

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.