scientific-agent-skills MCP — Cas d'usage, Installer & Démo en direct

Pourquoi l'utiliser

Fonctionnalités clés

133 skills spanning genomics, cheminformatics, molecular dynamics, clinical trials, ML training, and paper writing
REST API access recipes for 78+ public databases (ClinVar, COSMIC, ClinicalTrials.gov, FDA, PubMed, bioRxiv, arXiv)
Each skill includes runnable code examples and links to primary documentation
Claude routes between skills automatically based on the task domain

Démo en direct

Aperçu en pratique

scientific-agent-skill.replay ▶ prêt

0/0

Installer

Choisissez votre client

~/Library/Application Support/Claude/claude_desktop_config.json · Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "scientific-agent-skill": {
      "command": "git",
      "args": [
        "clone",
        "https://github.com/K-Dense-AI/scientific-agent-skills",
        "~/.claude/skills/scientific-agent-skills"
      ],
      "_inferred": true
    }
  }
}

Ouvrez Claude Desktop → Settings → Developer → Edit Config. Redémarrez après avoir enregistré.

~/.cursor/mcp.json · .cursor/mcp.json

{
  "mcpServers": {
    "scientific-agent-skill": {
      "command": "git",
      "args": [
        "clone",
        "https://github.com/K-Dense-AI/scientific-agent-skills",
        "~/.claude/skills/scientific-agent-skills"
      ],
      "_inferred": true
    }
  }
}

Cursor utilise le même schéma mcpServers que Claude Desktop. La config projet l'emporte sur la globale.

VS Code → Cline → MCP Servers → Edit

{
  "mcpServers": {
    "scientific-agent-skill": {
      "command": "git",
      "args": [
        "clone",
        "https://github.com/K-Dense-AI/scientific-agent-skills",
        "~/.claude/skills/scientific-agent-skills"
      ],
      "_inferred": true
    }
  }
}

Cliquez sur l'icône MCP Servers dans la barre latérale Cline, puis "Edit Configuration".

~/.codeium/windsurf/mcp_config.json

{
  "mcpServers": {
    "scientific-agent-skill": {
      "command": "git",
      "args": [
        "clone",
        "https://github.com/K-Dense-AI/scientific-agent-skills",
        "~/.claude/skills/scientific-agent-skills"
      ],
      "_inferred": true
    }
  }
}

Même format que Claude Desktop. Redémarrez Windsurf pour appliquer.

~/.continue/config.json

{
  "mcpServers": [
    {
      "name": "scientific-agent-skill",
      "command": "git",
      "args": [
        "clone",
        "https://github.com/K-Dense-AI/scientific-agent-skills",
        "~/.claude/skills/scientific-agent-skills"
      ]
    }
  ]
}

Continue utilise un tableau d'objets serveur plutôt qu'une map.

~/.config/zed/settings.json

{
  "context_servers": {
    "scientific-agent-skill": {
      "command": {
        "path": "git",
        "args": [
          "clone",
          "https://github.com/K-Dense-AI/scientific-agent-skills",
          "~/.claude/skills/scientific-agent-skills"
        ]
      }
    }
  }
}

Ajoutez dans context_servers. Zed recharge à chaud à la sauvegarde.

claude mcp add scientific-agent-skill -- git clone https://github.com/K-Dense-AI/scientific-agent-skills ~/.claude/skills/scientific-agent-skills

Une seule ligne. Vérifiez avec claude mcp list. Supprimez avec claude mcp remove.

Cas d'usage

Usages concrets : scientific-agent-skills

Run a single-cell RNA-seq analysis with Scanpy

👤 Computational biologists and bioinformatics postdocs ⏱ ~30 min intermediate

Quand l'utiliser : You have an .h5ad file and want QC, clustering, and UMAP without re-reading the Scanpy docs.

Prérequis

Scanpy installed in your env — pip install scanpy
An .h5ad dataset — Download from a public repo or use your own

Déroulement

Tell Claude the data and the goal

I have pbmc3k.h5ad. Use the scanpy skill to do QC, normalization, clustering, and a UMAP. Explain each step.✓ Copié

→ Claude calls the right Scanpy functions in the right order with sensible defaults
Iterate on parameters

Re-do clustering with resolution 0.8 and show how cluster labels changed.✓ Copié

→ Parameter tweak without re-planning the full pipeline

Résultat : A reproducible notebook plus figures, using idiomatic Scanpy — no hallucinated function names.

Pièges

Generic ML advice from Claude that ignores domain conventions — Reference the skill by name: 'use the scanpy skill'

Combiner avec : filesystem

Build a structured literature review from PubMed + arXiv

👤 PhD students, research scientists ⏱ ~45 min intermediate

Quand l'utiliser : You need 30+ papers on a topic with abstracts and citation metadata, not just titles from Google.

Déroulement

Specify scope

Use the paper-lookup skill. Find all PubMed and bioRxiv papers on GLP-1 agonists for Alzheimer's in the last 3 years.✓ Copié

→ Claude hits the right APIs with correct query syntax
Cluster by theme

Cluster by hypothesis (neuroinflammation, vascular, direct neuronal) and give me the top 3 papers per cluster.✓ Copié

→ Thematic grouping with citation-ready metadata

Résultat : A reviewable literature map with real DOIs, not fabricated citations.

Pièges

Claude hallucinates paper titles without the skill — Always verify DOIs — have Claude fetch one record to prove it's real

Combiner avec : fetch

Dock a small molecule to a target protein with DiffDock

👤 Medicinal chemists, drug discovery researchers ⏱ ~20 min advanced

Quand l'utiliser : You have a SMILES string and a PDB target and want a quick first-pass pose prediction.

Prérequis

DiffDock environment — Follow the DiffDock skill's env-setup recipe

Déroulement

Provide ligand and receptor

Using the diffdock skill, dock SMILES 'CC(=O)OC1=CC=CC=C1C(=O)O' into PDB 1ABC. Give me the top 5 poses with scores.✓ Copié

→ Claude runs the right DiffDock command with correct flags
Visualize

Generate a PyMOL script to render the top pose.✓ Copié

→ Runnable .pml file

Résultat : Pose predictions ready to feed into a downstream free-energy calculation.

Pièges

Claude invents flags that don't exist in DiffDock — The skill's reference folder has the real CLI — insist Claude consult it

Combiner avec : filesystem

Combinaisons

Associez-le à d'autres MCPs pour un effet X10

scientific-agent-skill + filesystem

Skills produce notebooks and figures; filesystem MCP stores and organizes the output

Save the Scanpy UMAP to results/figures/ and write a README for the experiment.✓ Copié

scientific-agent-skill + arxiv

Pair the paper-lookup skill with the arxiv MCP for richer citation graphs

Find arXiv papers citing the one I just read, grouped by which section they cite.✓ Copié

Outils

Ce que ce MCP expose

Outil	Entrées	Quand appeler	Coût
Bioinformatics (BioPython, Scanpy, pysam, gget, scVelo)	sequence / count matrix / BAM file	Sequence, genomics, or single-cell workflow	0 — local compute
Cheminformatics (RDKit, Datamol, DeepChem, DiffDock, OpenMM)	SMILES / PDB / MOL2	Small molecule, protein structure, or dynamics problem	0
Clinical databases (ClinVar, COSMIC, ClinicalTrials.gov, FDA)	gene / variant / trial ID	Looking up clinical evidence or trial status	0 — public APIs
Paper lookup (PubMed, bioRxiv, arXiv)	query string, date range	Literature search with real citations	0
ML training (PyTorch Lightning, Transformers, PyMC, TimesFM)	dataset + config	Building a model with idiomatic framework usage	0

Coût et limites

Coût d'exécution

Quota d'API: Public databases (NCBI, PubMed) have their own polite-use limits — typically 3 req/s
Tokens par appel: SKILL.md references are sizeable; expect 2-5k tokens loaded per domain touched
Monétaire: Free — skills are local files; only pay for compute you run
Astuce: Scope the prompt to one domain at a time so Claude doesn't load every SKILL.md.

Sécurité

Permissions, secrets, portée

Stockage des identifiants : No credentials in the skill itself; NCBI/PubMed work better with an email-in-env-var for polite rate limiting

Sortie de données : Only to the public science APIs you choose to query

Clinical data skills can hit PHI-adjacent records — make sure your usage complies with IRB/HIPAA when applicable.

Dépannage

Erreurs courantes et correctifs

Claude uses wrong function name from a skill's library

Tell it to re-read the skill's reference folder; the SKILL.md frontmatter should auto-load it.

Vérifier : ls ~/.claude/skills/scientific-agent-skills/<skill>/references/

API rate limit hit on NCBI

Add an email to NCBI_EMAIL env var and cap concurrency at 3 req/s.

Skill not invoked on a relevant prompt

Mention the library name explicitly ('use the rdkit skill') — auto-invocation is fuzzy across 133 skills.

Alternatives

scientific-agent-skills vs autres

Alternative	Quand l'utiliser	Compromis
ai-research-skill (Orchestra-Research)	You want ML-research infrastructure (training, distributed, inference) rather than wet-lab / clinical	More ML systems, less biology / chemistry domain depth
biomcp	You want an MCP server (live tools) rather than prompt-bundle skills	MCPs execute calls; skills just teach Claude to write the right code

Plus

Ressources

📖 Lire le README officiel sur GitHub

🐙 Voir les issues ouvertes

🔍 Parcourir les 400+ serveurs MCP et Skills