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Glama
coreymhudson

MCP Sequence Simulation Server

by coreymhudson

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
generate_dna_sequenceC

Generate random DNA sequences with specified parameters

generate_protein_sequenceB

Generate random protein sequences with specified parameters

mutate_sequenceC

Apply mutations to DNA or protein sequences

evolve_sequenceC

Simulate evolution of sequences over multiple generations

simulate_phylogenyC

Simulate phylogenetic tree and sequence evolution

simulate_fastq_fileB

Simulate FASTQ sequencing reads with realistic quality scores and error models based on NEAT methodology. Implementation inspired by: Stephens et al. (2016) 'Simulating Next-Generation Sequencing Datasets from Empirical Mutation and Sequencing Models.' PLOS ONE 11(11): e0167047. https://doi.org/10.1371/journal.pone.0167047

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

A3.5/5.0

Scored across 6 tools

Disambiguation5/5

Each tool has a clearly distinct purpose with no ambiguity. Tools target specific simulation tasks: sequence generation (DNA/protein), evolution (evolve/mutate), phylogeny simulation, and FASTQ file generation. The descriptions clearly differentiate their scopes, preventing misselection.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern (e.g., evolve_sequence, generate_dna_sequence, simulate_fastq_file). The naming convention is uniform throughout, using snake_case and clear action-object pairs, making the tool set predictable and readable.

Tool Count5/5

With 6 tools, the count is well-scoped for a sequence simulation server. Each tool earns its place by covering key aspects: sequence generation, mutation, evolution, phylogeny, and FASTQ simulation. This provides a focused yet comprehensive surface without being overwhelming.

Completeness4/5

The tool set covers core sequence simulation workflows effectively, including generation, mutation, evolution, phylogeny, and sequencing data. A minor gap is the lack of tools for analyzing or visualizing simulated data, but agents can work around this as the surface supports essential simulation tasks.

Maintenance

ActivityInactive
ResponsivenessNo issues