Skip to main content
Glama
Sign In
gnomAD MCP Server

gnomAD MCP Server

by koido
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_structural_variant_info

Retrieve structural variant information from gnomAD databases to analyze genomic data using dataset, reference genome, and variant ID parameters.

Instructions

[gnomAD API] Retrieve structural variant info (v2/v4) Args: dataset (str): SV dataset ID (gnomad_sv_r4/gnomad_sv_r2_1) reference_genome (str): Reference genome (GRCh37 or GRCh38) variantId (str): Structural variant ID Returns: dict: SV 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_structural_variant_info"
  }
}

Input Schema

NameRequiredDescriptionDefault
datasetYes
reference_genomeYes
variantIdYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • server.py:176-196 (handler)
    The get_structural_variant_info function handles the MCP tool request by calling run_query_with_metadata with the 'structural_variant' operation and the provided parameters.
    def get_structural_variant_info(
    dataset: str,
    reference_genome: str,
    variantId: str
) -> dict:
    """
    [gnomAD API] Retrieve structural variant info (v2/v4)
    Args:
        dataset (str): SV dataset ID (gnomad_sv_r4/gnomad_sv_r2_1)
        reference_genome (str): Reference genome (GRCh37 or GRCh38)
        variantId (str): Structural variant ID
    Returns:
        dict: SV info
    """

    variables = {
        'dataset': dataset,
        'reference_genome': reference_genome,
        'variantId': variantId,
        }
    return run_query_with_metadata('structural_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?

With no annotations provided, the description carries full burden but provides minimal behavioral context. It states it's a retrieval operation but doesn't mention authentication requirements, rate limits, error conditions, or what specific information is returned beyond 'SV info'. The API source (gnomAD) is mentioned but without 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?

Well-structured with purpose statement followed by Args and Returns sections. The description is appropriately sized with no redundant information. The front-loaded purpose statement is clear, though the parameter explanations could be more detailed given the 0% schema coverage.

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 documentation and mentions the API source. The existence of an output schema reduces the need to detail return values. However, for a retrieval tool with multiple sibling alternatives, more context about when to use this specific tool would improve completeness.

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?

With 0% schema description coverage, the description partially compensates by listing all three parameters with brief explanations. However, it doesn't provide format examples, valid values beyond basic types, or explain relationships between parameters (e.g., dataset must match reference genome). The parameter documentation is minimal but covers all required parameters.

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 structural variant info' with the specific resource (gnomAD API) and version scope (v2/v4). It distinguishes from siblings like 'get_variant_info' by specifying 'structural variant' type, but doesn't explicitly contrast with 'get_copy_number_variant_info' which might overlap.

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 on when to use this tool versus alternatives like 'get_variant_info' or 'get_copy_number_variant_info'. The description mentions dataset versions (v2/v4) but doesn't explain when to choose which version or how this differs from other variant retrieval tools in the sibling list.

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

Deploy Server

Other Tools