claude

bio-research

Connect to preclinical research tools and databases (literature search, genomics analysis, target prioritization) to accelerate early-stage life sciences R&D

2 on GitHubby Anthropicv1.2.0updated 21 days ago

Not in a marketplace yet, so it loads for one session with --plugin-dir.

Plugin bio-research in raisdev/skills-hub. Commands read from the repo's manifest — 20 days ago.

What it installs

Skills (6)

  • instrument-data-to-allotrope

    Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Out

  • nextflow-development

    Run nf-core bioinformatics pipelines (rnaseq, sarek, atacseq) on sequencing data. Use when analyzing RNA-seq, WGS/WES, or ATAC-seq data—either local FASTQs or public datasets from GEO/SRA. Triggers on nf-core, Nextflow, FASTQ analysis, variant calling, gene expression, differential expression, GEO r

  • scientific-problem-selection

    This skill should be used when scientists need help with research problem selection, project ideation, troubleshooting stuck projects, or strategic scientific decisions. Use this skill when users ask to pitch a new research idea, work through a project problem, evaluate project risks, plan research

  • scvi-tools

    Deep learning for single-cell analysis using scvi-tools. This skill should be used when users need (1) data integration and batch correction with scVI/scANVI, (2) ATAC-seq analysis with PeakVI, (3) CITE-seq multi-modal analysis with totalVI, (4) multiome RNA+ATAC analysis with MultiVI, (5) spatial t

  • single-cell-rna-qc

    Performs quality control on single-cell RNA-seq data (.h5ad or .h5 files) using scverse best practices with MAD-based filtering and comprehensive visualizations. Use when users request QC analysis, filtering low-quality cells, assessing data quality, or following scverse/scanpy best practices for si

  • start

    Set up your bio-research environment and explore available tools. Use when first getting oriented with the plugin, checking which literature, drug-discovery, or visualization MCP servers are connected, or surveying available analysis skills before starting a new project.

MCP servers (11)

  • pubmed

    connects to: https://pubmed.mcp.claude.com/mcp

  • biorender

    connects to: https://mcp.services.biorender.com/mcp

  • biorxiv

    connects to: https://hcls.mcp.claude.com/biorxiv/mcp

  • consensus

    connects to: https://mcp.consensus.app/mcp

  • c-trials

    connects to: https://hcls.mcp.claude.com/clinical_trials/mcp

  • chembl

    connects to: https://hcls.mcp.claude.com/chembl/mcp

  • synapse

    connects to: https://mcp.synapse.org/mcp

  • wiley

    connects to: https://connector.scholargateway.ai/mcp

  • owkin

    connects to: https://mcp.k.owkin.com/mcp

  • ot

    connects to: https://mcp.platform.opentargets.org/mcp

  • benchling
View source on GitHub raisdev.github.io

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