# Claude Code Biology Research

> ?? A comprehensive guide to using Claude Code as an AI-powered assistant for computational biology, bioinformatics, and biomedical research

- **Type:** MCP server
- **Install:** `agentstack add mcp-jeny-liu-claude-code-biology-research`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [Jeny-Liu](https://agentstack.voostack.com/s/jeny-liu)
- **Installs:** 0
- **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [Jeny-Liu](https://github.com/Jeny-Liu)
- **Source:** https://github.com/Jeny-Liu/claude-code-biology-research
- **Website:** https://github.com/Jeny-Liu/claude-code-biology-research

## Install

```sh
agentstack add mcp-jeny-liu-claude-code-biology-research
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

🧬 Claude Code for Biology Research
  
    A comprehensive guide to using Claude Code as an AI-powered assistant for computational biology, bioinformatics, and biomedical research
  
  
    
    
    
    
    
  
  
    
    
    
    
  
  
    
  
  

---

## 📋 Table of Contents

- [🌐 Overview](#-overview)
- [✨ Key Features](#-key-features)
- [📦 Installation](#-installation)
  - [System Requirements](#system-requirements)
  - [Installing Claude Code](#installing-claude-code)
  - [Authentication](#authentication)
  - [Proxy Configuration](#proxy-configuration)
  - [Verifying Installation](#verifying-installation)
- [🚀 Quick Start](#-quick-start)
  - [Your First Biology Session](#your-first-biology-session)
  - [Key CLI Commands](#key-cli-commands)
- [🧠 Skills for Biology Research](#-skills-for-biology-research)
  - [Built-in Skills](#built-in-skills)
  - [Custom Biology Skills](#custom-biology-skills)
  - [Skill Development Guide](#skill-development-guide)
- [🔌 MCP Servers](#-mcp-servers)
  - [What is MCP?](#what-is-mcp)
  - [Essential Biology MCP Servers](#essential-biology-mcp-servers)
  - [MCP Configuration Guide](#mcp-configuration-guide)
  - [Custom MCP Server Development](#custom-mcp-server-development)
- [🧪 Biology Workflows](#-biology-workflows)
  - [Genomics & Transcriptomics](#genomics--transcriptomics)
  - [Proteomics & Structural Biology](#proteomics--structural-biology)
  - [Literature Review & Meta-analysis](#literature-review--meta-analysis)
  - [Biological Image Analysis](#biological-image-analysis)
  - [Laboratory Protocol Design](#laboratory-protocol-design)
- [📝 Practical Examples](#-practical-examples)
  - [Example 1: RNA-seq Data Analysis](#example-1-rna-seq-data-analysis)
  - [Example 2: Protein Structure Retrieval](#example-2-protein-structure-retrieval)
  - [Example 3: Literature Review Automation](#example-3-literature-review-automation)
- [⚙️ Advanced Configuration](#️-advanced-configuration)
  - [Settings.json Deep Dive](#settingsjson-deep-dive)
  - [Custom Hooks](#custom-hooks)
  - [Environment Management](#environment-management)
- [🤝 Best Practices](#-best-practices)
- [📚 Resources & References](#-resources--references)
- [📄 License](#-license)

---

## 🌐 Overview

**Claude Code** is Anthropic's official command-line interface (CLI) for Claude, designed to be an **agentic AI coding assistant** that works directly in your terminal. For biology researchers and computational biologists, Claude Code represents a paradigm shift — it bridges the gap between biological domain knowledge and computational implementation.

Instead of switching between multiple tools, databases, and programming environments, you can:

1. **Describe your biology research task in natural language**
2. **Let Claude Code understand the context and generate appropriate code**
3. **Execute, debug, and refine analyses interactively**
4. **Automate repetitive bioinformatics workflows**
5. **Integrate with public biological databases and lab data systems**

### How It Works

Claude Code operates as an **agentic system** in your terminal:

```
You: "Download RNA-seq data from GEO accession GSE12345, perform differential expression analysis, and create a volcano plot"

Claude Code:
  ✓ Parses your request into actionable steps
  ✓ Uses MCP tools to query GEO database
  ✓ Downloads FASTQ/count data
  ✓ Writes Python/R script for DESeq2 analysis
  ✓ Executes the analysis
  ✓ Generates publication-quality figures
  ✓ Summarizes results
```

This guide covers everything from installation to advanced workflow orchestration for biology research.

---

## ✨ Key Features

| Feature | Biology Research Application |
|---------|---------------------------|
| **🧬 Natural Language to Code** | Describe biology concepts; Claude writes Python/R/Bash scripts |
| **🔗 MCP Tool Integration** | Direct access to NCBI, UniProt, PDB, PubMed, and more |
| **📊 Multi-modal Support** | Analyze microscope images, gel photos, and plots |
| **🔄 Autonomous Workflows** | End-to-end analysis pipelines with iterative refinement |
| **📝 Academic Writing** | Draft manuscripts, methods sections, and literature reviews |
| **📦 Reproducible Science** | Generate Conda/Docker environments, package requirements |
| **🗂️ Project Management** | Organize code, data, and results in structured projects |
| **🤝 Collaborative** | Git-native, team-friendly, shareable analysis scripts |

---

## 📦 Installation

### System Requirements

| Requirement | Minimum | Recommended |
|------------|---------|-------------|
| **OS** | macOS 10.15+, Ubuntu 20.04+, Windows 10+ (via WSL2) | Latest stable |
| **Node.js** | 18.x | 20.x LTS |
| **npm** | 8.x | 10.x+ |
| **Python** | 3.8 | 3.11+ (for bioinformatics) |
| **R** | 4.0 | 4.3+ (for Bioconductor) |
| **Disk Space** | 1 GB | 10 GB+ (for biological databases) |
| **RAM** | 4 GB | 16 GB+ |
| **Internet** | Required for installation and API access | Broadband |

### Installing Claude Code

#### Method 1: npm (Recommended)

```bash
# Install globally
npm install -g @anthropic-ai/claude-code

# Or use npx for one-off usage
npx @anthropic-ai/claude-code
```

#### Method 2: VS Code Extension

Install the [Claude Code Extension](https://marketplace.visualstudio.com/items?itemName=anthropic.claude-code) from the VS Code Marketplace, or:

```bash
# Install via VS Code CLI
code --install-extension anthropic.claude-code
```

#### Method 3: Homebrew (macOS/Linux)

```bash
brew install anthropic/claude-code/claude-code
```

#### Method 4: Direct Download

Download the latest release from [Claude Code Releases](https://github.com/anthropics/claude-code/releases).

### Authentication

Claude Code requires an Anthropic API key:

```bash
# Set your API key
export ANTHROPIC_API_KEY="sk-ant-xxxxxxxxxxxx"

# Or save it to ~/.claude/.env for persistence
echo 'ANTHROPIC_API_KEY="sk-ant-xxxxxxxxxxxx"' >> ~/.claude/.env
```

> 💡 **For biology researchers:** If your institution has an enterprise Anthropic account, request an API key through your institutional IT department. Consider security and data privacy — do not share your API key.

#### Getting Your API Key

1. Visit [console.anthropic.com](https://console.anthropic.com)
2. Create an account or sign in
3. Navigate to **API Keys**
4. Create a new key
5. Copy the key and store it securely

### Proxy Configuration

If your institution uses a proxy (common in research environments):

```bash
# HTTP/HTTPS proxy
export HTTP_PROXY="http://proxy.your-institution.edu:8080"
export HTTPS_PROXY="http://proxy.your-institution.edu:8080"

# Configure git proxy (for cloning repos)
git config --global http.proxy http://proxy.your-institution.edu:8080
git config --global https.proxy http://proxy.your-institution.edu:8080

# Configure npm proxy
npm config set proxy http://proxy.your-institution.edu:8080
npm config set https-proxy http://proxy.your-institution.edu:8080
```

### Verifying Installation

```bash
# Check version
claude --version

# Start an interactive session
claude

# Run a quick test
claude -p "Write a Python script that prints the reverse complement of a DNA sequence: ATGCGTAC"
```

**Expected output:**
```python
def reverse_complement(seq):
    """Return the reverse complement of a DNA sequence."""
    complement = {'A': 'T', 'T': 'A', 'C': 'G', 'G': 'C'}
    return ''.join(complement.get(base, base) for base in reversed(seq))

seq = "ATGCGTAC"
result = reverse_complement(seq)
print(f"Original: {seq}")
print(f"Reverse complement: {result}")
# Output: Original: ATGCGTAC
#         Reverse complement: GTACGCAT
```

---

## 🚀 Quick Start

### Your First Biology Session

```bash
# Start Claude Code
claude
```

Once inside the interactive session, try these biology research prompts:

```
1️⃣ "Download the human genome assembly hg38 FASTA file using curl and index it with samtools"

2️⃣ "Write a Python script using BioPython to parse a GenBank file and extract CDS features.
     Save it as parse_genbank.py"

3️⃣ "Search PubMed for recent papers on CRISPR prime editing and summarize the top 5"

4️⃣ "Create a volcano plot from this differential expression CSV file using ggplot2 in R"
```

### Key CLI Commands

| Command | Purpose | Biology Research Use |
|---------|---------|---------------------|
| `claude` | Start interactive session | Begin a research analysis session |
| `claude -p "prompt"` | Run one-off command | Quick sequence manipulation |
| `claude --model "claude-sonnet-4-20250514"` | Specify model | Use latest model for complex analyses |
| `claude -e "python script.py" "` | Edit existing file | Refine an analysis script |
| `claude -i "path/to/file"` | Include system prompt | Load institutional protocols |
| `/clear` | Clear session | Reset for new analysis |
| `/help` | Show help | Browse available commands |
| `/init` | Init project config | Set up project-specific settings |
| `/fast` | Toggle fast mode | Quick responses for simple tasks |
| `/loop` | Repeat command periodically | Monitor long-running analyses |

> 💡 **Pro tip:** Use `claude -p "prompt"` in shell scripts to build automated bioinformatics pipelines!

---

## 🧠 Skills for Biology Research

Claude Code's **Skills** are specialized capabilities — think of them as plugins that give Claude expert-level abilities in specific domains. Skills can be loaded via `/skill-name` in CLI or invoked programmatically.

### Built-in Skills

Here are the most valuable built-in skills for biology research:

#### 📚 Literature & Writing Skills

| Skill | Invocation | Description | Biology Use Case |
|-------|-----------|-------------|-----------------|
| **systematic-literature-review** | `/systematic-literature-review` | Multi-source literature search, quality scoring, and auto-generation of structured reviews | Systematic reviews, meta-analyses, related work sections |
| **academic-writing-polisher** | `/academic-writing-polisher` | Polish academic writing with domain-aware style corrections | Manuscript refinement, grant proposals |
| **paper-write-sci** | `/paper-write-sci` | Generate scientific paper drafts from data and outlines | Full manuscript drafting |
| **paper-select-journal** | `/paper-select-journal` | Recommend target journals based on manuscript content | Journal selection guidance |
| **review-papers** | `/review-papers` | Peer review simulation with structured feedback | Pre-submission review |
| **paper-explain-figures** | `/paper-explain-figures` | Interpret scientific figures and create accessible descriptions | Figure legends, accessibility |

#### 🔬 Bioinformatics & Lab Skills

| Skill | Invocation | Description |
|-------|-----------|-------------|
| **chem-vis** | `/chem-vis` | Generate 2D/3D molecular visualizations from SMILES/names |
| **thesis-review** | `/thesis-review` | Comprehensive thesis structure and content review |
| **systematic-literature-review** | `/systematic-literature-review` | AI-powered literature survey with quality scoring |

#### 🛠️ Development & Workflow Skills

| Skill | Invocation | Description |
|-------|-----------|-------------|
| **code-review** | `/code-review` | Review bioinformatics code for correctness and efficiency |
| **simplify** | `/simplify` | Optimize and refactor analysis scripts |
| **verify** | `/verify` | Verify that code changes work as expected |
| **deep-research** | `/deep-research` | Multi-source deep research with fact-checking and citations |
| **init** | `/init` | Project scaffolding |
| **run** | `/run` | Launch and interact with project applications |

### Custom Biology Skills

You can create custom skills for your specific biology research needs:

```bash
# Create a new skill
claude -p "Create a custom skill for single-cell RNA-seq analysis workflow automation"
```

Example custom skill structure for a **single-cell RNA-seq analysis skill**:

📁 Custom Skill Example: scRNA-seq Analysis Skill (Click to expand)

```markdown
# Skill: scrna-seq-analysis

## Description
Automated single-cell RNA-seq analysis pipeline using ScanPy and Seurat

## Triggers
- "analyze single cell data"
- "scRNA-seq workflow"
- "single cell clustering"

## Steps
1. Quality control: Filter cells based on gene counts and mitochondrial content
2. Normalization: Log-normalize and identify highly variable genes
3. Dimensionality reduction: PCA, UMAP, t-SNE
4. Clustering: Leiden clustering with resolution optimization
5. Marker identification: Differential expression per cluster
6. Cell type annotation: Automated annotation using reference databases
7. Visualization: UMAP plots, heatmaps, dotplots

## Dependencies
- scanpy>=1.9
- anndata>=0.9
- leidenalg
- matplotlib>=3.6
- pandas>=1.5
```

### Skill Development Guide

To create biology-focused skills:

```bash
# Step 1: Use the skill-creator
# In Claude Code:
/skill-creator

# Step 2: Describe your biology workflow
# "Create a skill for ChIP-seq peak calling and motif analysis"

# Step 3: The skill will be registered and available via /your-skill-name
```

**Skill Design Principles for Biology:**

| Principle | Description | Example |
|-----------|-------------|---------|
| **Domain-specific** | Focus on one biological analysis type | "ChIP-seq analysis" not "sequencing analysis" |
| **Reproducible** | Include version-locked dependencies | `scanpy==1.9.3` |
| **Documented** | Clear input/output specifications | Input: FASTQ files, Output: peak BED files |
| **Modular** | Composable with other skills | QC skill → Alignment skill → Peak calling skill |

---

## 🔌 MCP Servers

### What is MCP?

**MCP (Model Context Protocol)** is an open standard that allows Claude Code to connect directly with external tools, databases, and services. Think of MCP servers as **"adapters"** that give Claude real-time access to biological data sources and computational tools.

**How MCP works with Claude Code:**

```
┌─────────────┐    MCP Protocol    ┌──────────────┐    HTTP/API    ┌──────────────┐
│  Claude Code │ ◄──────────────► │  MCP Server  │ ◄────────────► │  NCBI / UniProt / PDB / PubMed  │
│  (AI Engine) │                  │  (Adapter)   │               │  (Databases)  │
└─────────────┘                  └──────────────┘               └──────────────┘
```

### Essential Biology MCP Servers

#### 1️⃣ **NCBI/BLAST MCP Server**

Access National Center for Biotechnology Information databases and BLAST search:

```json
{
  "mcpServers": {
    "ncbi-biology": {
      "command": "uvx",
      "args": ["ncbi-mcp-server"],
      "env": {
        "NCBI_API_KEY": "your_ncbi_api_key",
        "EMAIL": "your.email@institution.edu"
      }
    }
  }
}
```

**Capabilities:**
- `search_nucleotide(query)` — Search nucleotide databases
- `search_protein(query)` — Search protein databases  
- `run_blast(sequence, database)` — BLAST sequence search
- `fetch_genbank(accession)` — Download GenBank records
- `fetch_fasta(accession)` — Download FASTA sequences
- `search_pubmed(query)` — PubMed literature search
- `search_geo(query)` — GEO dataset search

> 🔑 **NCBI API Key:** Register at [ncbi.nlm.nih.gov](https://www.ncbi.nlm.nih.gov/account/) for higher rate limits. Without a key, you're limited to 3 requests/second; with a key, 10 requests/second.

#### 2️⃣ **UniProt/PDB MCP Server**

Access protein sequence, structure, and functional data:

```json
{
  "mcpServers": {
    "uniprot-pdb": {
      "command": "uvx",
      "args": ["uniprot-mcp-server"]
    }
  }
}
```

**Capabilities:**
- `search_uniprot(query)` — Search UniProtKB
- `get_protein(accession)` — Retrieve protein entry
- `fetch_pdb(pdb_id)` — Download PDB structure files
- `search_pdb(query)` — Search PDB for structures
- `get_alphafold(uniprot_id)` — Retrieve AlphaFold predictions
- `get_protein_features(accession)` — Domain, site, and feature annotations
- `search_by_sequence(sequence)` — Sequence similarity search

#### 3️⃣ **PubMed MCP Server**

Advanced literature mining and retrieval:

```json
{
  "mcpServers": {
    "pubmed-mcp": {
      "command": "npx",
      "a

…

## Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [Jeny-Liu](https://github.com/Jeny-Liu)
- **Source:** [Jeny-Liu/claude-code-biology-research](https://github.com/Jeny-Liu/claude-code-biology-research)
- **License:** MIT
- **Homepage:** https://github.com/Jeny-Liu/claude-code-biology-research

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** yes
- **Filesystem access:** no
- **Shell / process execution:** yes
- **Environment & secrets:** yes
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/mcp-jeny-liu-claude-code-biology-research
- Seller: https://agentstack.voostack.com/s/jeny-liu
- Browse the marketplace: https://agentstack.voostack.com/browse

---
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