MCP Sequence Simulation Server MCP Server

MCP Sequence Simulation Server

An MCP (Model Context Protocol) server for simulating DNA and amino acid sequences using various evolutionary models and algorithms. This server provides powerful tools for sequence generation, mutation simulation, evolutionary modeling, and phylogenetic analysis.

Features

🧬 DNA Sequence Generation

• Random DNA Generation: Generate sequences with specified GC content
• Markov Chain Models: Context-dependent sequence generation
• Codon-Biased Generation: Realistic protein-coding sequences
• Customizable Parameters: Length, GC content, seed for reproducibility

📊 FASTQ Sequencing Simulation

• NGS Read Simulation: Generate realistic next-generation sequencing reads
• Platform-Specific Models: Illumina, 454, Ion Torrent, and PacBio quality models
• Paired-End Support: Both single-end and paired-end sequencing reads
• Error Modeling: Configurable sequencing error rates with realistic quality scores
• Coverage Control: Generate reads to achieve specified coverage depths
• NEAT-Based: Implementation inspired by published NEAT methodology

🧭 Protein Sequence Generation

• Random Protein Generation: Uniform amino acid distribution
• Hydrophobic-Biased: Membrane protein-like sequences
• Disorder-Prone: Intrinsically disordered protein sequences
• Custom Composition: User-defined amino acid frequencies

🔬 Sequence Mutation

• Substitution Mutations: Point mutations with transition/transversion bias
• Insertion/Deletion Events: Indel mutations
• Multiple Iterations: Track changes over time
• Both DNA and Protein: Support for nucleotide and amino acid sequences

🌳 Evolutionary Simulation

• Population Evolution: Simulate populations over generations
• Selection Pressure: Configurable fitness functions
• Lineage Tracking: Follow individual evolutionary paths
• Fitness Functions: GC content, length, hydrophobicity targets

🌲 Phylogenetic Simulation

• Tree-Based Evolution: Simulate sequences on phylogenetic trees
• Multiple Substitution Models: JC69, K80, HKY85, GTR
• Molecular Clock: Uniform or variable evolutionary rates
• Multiple Output Formats: FASTA, NEXUS, PHYLIP

Installation

npm install
npm run build

Usage

With Claude Code

./start-claude.sh

Manual Configuration

Add to your Claude Code MCP configuration:

{
  "mcpServers": {
    "sequence-simulation": {
      "command": "node",
      "args": ["dist/server.js"],
      "cwd": "/path/to/mcp-sequence-simulation"
    }
  }
}

Available Tools

1. Generate DNA Sequence

Generate random DNA sequences with various models.

Parameters:

• length (required): Sequence length
• gcContent (optional): GC content ratio (0-1, default: 0.5)
• count (optional): Number of sequences (default: 1)
• model (optional): "random", "markov", or "codon-biased"
• seed (optional): Random seed for reproducibility
• outputFormat (optional): "fasta" or "plain"

Example:

{
  "length": 1000,
  "gcContent": 0.6,
  "count": 5,
  "model": "markov",
  "outputFormat": "fasta"
}

2. Generate Protein Sequence

Generate random protein sequences with various biases.

Parameters:

• length (required): Sequence length
• count (optional): Number of sequences (default: 1)
• model (optional): "random", "hydrophobic-bias", or "disorder-prone"
• composition (optional): Custom amino acid frequencies
• seed (optional): Random seed
• outputFormat (optional): "fasta" or "plain"

Example:

{
  "length": 200,
  "count": 3,
  "model": "hydrophobic-bias",
  "outputFormat": "fasta"
}

3. Simulate FASTQ File

Simulate FASTQ sequencing reads with realistic quality scores and error models.

Parameters:

• referenceSequence (required): Reference DNA sequence to generate reads from
• readLength (required): Length of each sequencing read (50-300 bp)
• coverage (required): Target sequencing coverage depth (1-1000x)
• readType (optional): "single-end" or "paired-end" (default: "single-end")
• insertSize (optional): Mean insert size for paired-end reads (default: 300)
• insertSizeStd (optional): Standard deviation of insert size (default: 50)
• errorRate (optional): Base calling error rate 0-0.1 (default: 0.01)
• qualityModel (optional): "illumina", "454", "ion-torrent", or "pacbio" (default: "illumina")
• mutationRate (optional): Rate of true mutations 0-0.05 (default: 0.001)
• seed (optional): Random seed for reproducibility
• outputFormat (optional): "fastq" or "json" (default: "fastq")

Example:

{
  "referenceSequence": "ATCGATCGATCGATCGATCGATCGATCGATCGATCG",
  "readLength": 150,
  "coverage": 30,
  "readType": "paired-end",
  "errorRate": 0.01,
  "qualityModel": "illumina"
}

Citation: Based on Stephens et al. (2016) PLOS ONE 11(11): e0167047.

4. Mutate Sequence

Apply mutations to exist