"A service for finding research papers and literature on deep learning" matching MCP servers:

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.

Provides protein family, domain, and functional annotation using InterProScan, supporting local or API backends.

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.

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.

Enables LLM agents to search biomedical literature, retrieve article details, find related papers, manage caching, and download open-access full texts through MCP with structured, agent-friendly responses.

▎ Provides 32 tools for plant-genomics locus lookup across 11 free public backends (Ensembl Plants, Phytozome, UniProtKB, Europe PMC, QuickGO, NCBI BLAST, Gramene, KEGG, STRING-DB, ATTED-II, BAR). Takes a TAIR-style locus plus optional organism and returns gene metadata, functional/pathway annotation, interactions, co-expression, and literature — in single-locus, batch, and cross-source synthesis.

MCP server offering verified bioinformatics tools for sequence utilities and statistics, backed by BioPython/scipy. Enables AI agents to perform accurate GC content, translation, ORF finding, motif scanning, and statistical tests through natural language.

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.

Enables unified access to 110 life science APIs and databases, including genomics, proteomics, chemistry, literature, and clinical data. Users can query genes, proteins, compounds, pathways, and more through natural language.

A high-performance MCP server that gives LLMs access to 25 biomedical tools federated across 50+ upstream APIs for genes, variants, drugs, diseases, literature, clinical trials, and structural biology.

A bioinformatics MCP server that connects AI clients to over 30 life science databases and 32 curated tools for research, drug discovery, and clinical analysis.

Predicts CRISPR gene dependencies and drug targets by integrating literature, regulatory/PPI networks, and genome-scale metabolic models.

Enables AI coding agents to search academic papers, resolve biomedical entities, mine relations, and traverse citation graphs using Semantic Scholar and PubTator3, with local caching for reproducibility.

Server to search PubMed (PubMed is a free, online database that allows users to search for biomedical and life sciences literature). I have created on a day MCP came out but was on vacation, I saw someone post similar server in your DB, but figured to post mine.

BioMCP is an open-source MCP server that connects any AI assistant to 15 open bioinformatics databases with zero configuration. It provides 23 tools for literature, sequences, BLAST, structures, enrichment, annotations, genomes, interactions, variants, domains, compounds, and single-cell data.

Provides AI-powered access to major biological databases for GWAS and bioinformatics research. Enables natural language queries for protein, gene, variant, pathway, and drug discovery analysis.

Enables querying and browsing ontologies from the EBI Ontology Lookup Service, including searching for terms, retrieving term details, and navigating ontology hierarchies via natural language.

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.