"Data science and deep learning papers" matching MCP servers:

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.

Enables AI agents to retrieve and analyze breeding data from BrAPI-compliant databases through shared tools, with human-in-the-loop approval and verification.

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.

Parses MS-DIAL binary lipidomics outputs and runs standard analyses server-side, returning compact summaries so an LLM can drive full lipidomics analysis without exposing raw matrices.

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.

Enables users to search multiple public life-science data repositories (GEO, ENA, CELLxGENE, PRIDE, DataCite) with a single query, returning a unified ranked list of datasets with ontology-expanded terms and per-source error reporting.

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.

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.

Dog-specific aging tools: HAGR dog rows (AnAge/DrugAge/GenAge), dog orthologs of aging genes via Ensembl, FDA Km dose translation, Dog Aging Project codebooks, NIH RePORTER grants, BM25 search over 3,500+ canine aging papers, FDA CVM FOI summaries with quote-grounded PK and safety data, and an intervention dossier that composes them. Installs with uvx; downloads its database on first run.

Enables life-science research by providing search and retrieval across linked publications, clinical trials, drugs, genes, regulatory approvals, and patents through MCP clients.

Annotate variants by with a deep and rich set of data. Can annotate: genetic change, rsID, CAid, HGVS (g./c./p.), protein change.

Enables deep probabilistic analysis of single-cell omics data using scvi-tools through natural language. Supports SCVI for scRNA-seq analysis, SCANVI for cell type annotation, TOTALVI for multi-modal RNA/protein data, and PEAKVI for scATAC-seq analysis.

Enables querying HERB 2.0's Traditional Chinese Medicine knowledge base for herbs, ingredients, gene targets, diseases, PubMed-cited papers, and GEO transcriptomic experiments, with each relationship tagged by evidence tier.

Connects AI agents to a hosted remote MCP endpoint that searches academic papers, verifies references and retraction status, retrieves research datasets, grants, and biological or chemical data, and generates scientific figures across 50+ upstream sources. Supports OAuth sign-in with per-tool credit accounting, structured error reporting, and source attribution for results.

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

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.

🔍 Enable AI assistants to search and access bioRxiv papers through a simple MCP interface. The bioRxiv MCP Server provides a bridge between AI assistants and bioRxiv's preprint repository through the Model Context Protocol (MCP). It allows AI models to search for biology preprints and access their

Enables searching for academic papers and preprints across multiple platforms including Semantic Scholar, arXiv, PubMed, and CrossRef. It provides access to research records, DOI lookups, and journal metadata through a unified interface deployed on Cloudflare Workers.