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gnomAD MCP Server

gnomAD MCP Server

by koido
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_variant_info

Retrieve variant information from gnomAD databases to analyze genetic variations across populations and reference genomes.

Instructions

[gnomAD API] Retrieve variant information (v2/v3/v4) Args: dataset (str): gnomAD dataset ID (gnomad_r4/gnomad_r3/gnomad_r2_1) reference_genome (str): Reference genome (GRCh37 or GRCh38) variantId (str): Variant ID (e.g. 1-55051215-G-GA) Returns: dict: variant info

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "dataset": "<dataset>",
      "reference_genome": "<reference_genome>",
      "variantId": "<variantId>"
    },
    "name": "get_variant_info"
  }
}

Input Schema

NameRequiredDescriptionDefault
datasetYes
reference_genomeYes
variantIdYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • server.py:100-121 (handler)
    The get_variant_info function serves as the MCP tool handler. It is decorated with @mcp.tool() and uses the helper run_query_with_metadata to perform the data retrieval.
    @mcp.tool()
def get_variant_info(
    dataset: str,
    reference_genome: str,
    variantId: str
) -> dict:
    """
    [gnomAD API] Retrieve variant information (v2/v3/v4)
    Args:
        dataset (str): gnomAD dataset ID (gnomad_r4/gnomad_r3/gnomad_r2_1)
        reference_genome (str): Reference genome (GRCh37 or GRCh38)
        variantId (str): Variant ID (e.g. 1-55051215-G-GA)
    Returns:
        dict: variant info
    """

    variables = {
        'dataset': dataset,
        'reference_genome': reference_genome,
        'variantId': variantId,
    }
    return run_query_with_metadata('variant', variables)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It states this is a retrieval operation but doesn't disclose behavioral traits like authentication requirements, rate limits, error handling, or what specific variant information is returned. The mention of 'gnomAD API' hints at an external service but gives no operational details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured and front-loaded with the core purpose, followed by parameter and return details. It uses minimal sentences efficiently, though the Args/Returns formatting is slightly verbose. Every sentence adds value without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 3 parameters with 0% schema coverage and no annotations, the description provides basic parameter context but lacks behavioral and usage details. An output schema exists ('dict: variant info'), so return values needn't be explained. However, for a tool interacting with an external API and multiple sibling alternatives, more contextual guidance would be beneficial.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It adds basic semantics by explaining each parameter's purpose (e.g., 'dataset' as gnomAD dataset ID, 'variantId' format example), but doesn't provide enums, constraints, or detailed formatting rules. This partially addresses the schema gap but leaves significant ambiguity.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Retrieve variant information' with specific API context ('gnomAD API') and version scope ('v2/v3/v4'). It distinguishes from siblings like 'get_clinvar_variant_info' and 'get_structural_variant_info' by focusing on general gnomAD variant data, but doesn't explicitly contrast them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. With many sibling tools available (e.g., 'get_clinvar_variant_info', 'get_structural_variant_info'), the description lacks any indication of appropriate contexts, prerequisites, or exclusions for this specific variant retrieval tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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