biotools-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
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
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| seq_gc_contentA | Compute GC content of a nucleotide sequence as a percentage (0-100). |
| seq_reverse_complementA | Compute the reverse complement of a nucleotide sequence (DNA or RNA). |
| seq_translateA | Translate a nucleotide sequence to protein using an NCBI genetic code table. |
| seq_orf_finderA | Find open reading frames (forward strand, frames 0-2) in a nucleotide sequence. |
| seq_motif_scanA | Scan a nucleotide sequence for IUPAC motif occurrences (supports bracket groups). |
| seq_statsA | Compute sequence length, mono/dinucleotide composition, and GC skew. |
| stats_describeA | Compute descriptive statistics (n, min, max, mean, median, variance, std, skew, kurtosis). |
| stats_t_testA | Run a two-sample Student or Welch t-test with Cohen's d effect size. |
| stats_chi_squareA | Run a chi-square test of independence on a contingency table (Yates correction optional). |
| stats_mann_whitneyA | Run a Mann-Whitney U test on two independent groups. |
| stats_correlationA | Compute Pearson or Spearman correlation between two paired variables. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 11 tools
Each tool has a distinct purpose within its domain. The seq_* tools cover motif scanning, GC content, reverse complement, translation, ORF finding, and sequence stats with no overlap. The stats_* tools cover descriptive statistics, t-test, chi-square, Mann-Whitney, and correlation, also without ambiguity. The two domains are clearly separated by prefix and description.
Tool names follow a consistent domain-prefix pattern: seq_ for sequence operations and stats_ for statistical tests. However, within each prefix, the naming style is mixed (e.g., seq_translate is a verb, seq_orf_finder is a noun; stats_describe is a verb, stats_t_test is a noun). This minor inconsistency lowers the score from 5 to 4, but the prefix convention makes names predictable.
With 11 tools, the server is well-scoped for a bioinformatics toolkit. It covers a reasonable set of sequence analysis functions and common statistical tests without being bloated. The count falls well within the ideal range for a focused utility server.
The tool surface covers core sequence operations (translation, reverse complement, GC content, motif scanning, ORF finding, and stats) and common statistical tests (descriptive, t-test, chi-square, Mann-Whitney, correlation). Minor gaps exist, such as sequence alignment or advanced statistical tests like ANOVA, but agents can perform most basic workflows without dead ends.