gnomAD MCP Server
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
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| searchC | Search for genes, variants, or regions in gnomAD |
| get_geneC | Get detailed information about a gene including constraint scores |
| get_variantC | Get detailed information about a specific variant |
| get_variants_in_geneC | Get all variants in a specific gene |
| get_transcriptC | Get information about a specific transcript |
| get_region_variantsC | Get variants in a specific genomic region |
| get_coverageC | Get coverage information for a gene |
| get_structural_variantsC | Get structural variants in a genomic region |
| get_mitochondrial_variantsC | Get mitochondrial variants |
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 9 tools
Most tools have distinct purposes targeting specific genomic entities (e.g., genes, variants, regions), but some overlap exists between 'get_variants_in_gene' and 'get_region_variants' which could cause confusion when querying gene regions. The descriptions help clarify, but the boundaries aren't perfectly clear.
All tool names follow a consistent 'verb_noun' pattern with 'get_' or 'search' prefixes, using snake_case uniformly. This predictability makes it easy for agents to understand and select tools without naming confusion.
With 9 tools, this server is well-scoped for querying genomic data from gnomAD. Each tool serves a specific purpose (e.g., coverage, genes, variants), and the count aligns with the domain's complexity without being overwhelming or insufficient.
The toolset covers core query operations for genes, variants, transcripts, and regions, with a general search function. Minor gaps exist, such as no explicit tools for filtering or aggregating results, but agents can work around this using the provided tools for most workflows.