scientific-agent-skills MCP — Casos de uso, Instalar & Demo ao vivo

Por que usar

Principais recursos

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

Demo ao vivo

Como fica na prática

scientific-agent-skill.replay ▶ pronto

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Instalar

Escolha seu cliente

~/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
    }
  }
}

Abra Claude Desktop → Settings → Developer → Edit Config. Reinicie após salvar.

~/.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 usa o mesmo esquema mcpServers que o Claude Desktop. Config de projeto vence a global.

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
    }
  }
}

Clique no ícone MCP Servers na barra lateral do Cline, depois "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
    }
  }
}

Mesmo formato do Claude Desktop. Reinicie o Windsurf para aplicar.

~/.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"
      ]
    }
  ]
}

O Continue usa um array de objetos de servidor em vez de um 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"
        ]
      }
    }
  }
}

Adicione em context_servers. Zed recarrega automaticamente ao salvar.

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

Uma linha só. Verifique com claude mcp list. Remova com claude mcp remove.

Casos de uso

Usos do mundo real: scientific-agent-skills

Run a single-cell RNA-seq analysis with Scanpy

👤 Computational biologists and bioinformatics postdocs ⏱ ~30 min intermediate

Quando usar: You have an .h5ad file and want QC, clustering, and UMAP without re-reading the Scanpy docs.

Pré-requisitos

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

Fluxo

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.✓ Copiado

→ 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.✓ Copiado

→ Parameter tweak without re-planning the full pipeline

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

Armadilhas

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

Combine com: filesystem

Build a structured literature review from PubMed + arXiv

👤 PhD students, research scientists ⏱ ~45 min intermediate

Quando usar: You need 30+ papers on a topic with abstracts and citation metadata, not just titles from Google.

Fluxo

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.✓ Copiado

→ 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.✓ Copiado

→ Thematic grouping with citation-ready metadata

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

Armadilhas

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

Combine com: fetch

Dock a small molecule to a target protein with DiffDock

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

Quando usar: You have a SMILES string and a PDB target and want a quick first-pass pose prediction.

Pré-requisitos

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

Fluxo

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.✓ Copiado

→ Claude runs the right DiffDock command with correct flags
Visualize

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

→ Runnable .pml file

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

Armadilhas

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

Combine com: filesystem

Combinações

Combine com outros MCPs para 10× de alavancagem

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.✓ Copiado

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.✓ Copiado

Ferramentas

O que este MCP expõe

Ferramenta	Entradas	Quando chamar	Custo
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

Custo e limites

O que custa rodar

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

Segurança

Permissões, segredos, alcance

Armazenamento de credenciais: No credentials in the skill itself; NCBI/PubMed work better with an email-in-env-var for polite rate limiting

Saída de dados: 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.

Solução de problemas

Erros comuns e correções

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.

Verificar: 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.

Alternativas

scientific-agent-skills vs. outros

Alternativa	Quando usar	Troca
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

Mais

Recursos

📖 Leia o README oficial no GitHub

🐙 Ver issues abertas

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