Skip to main content
Glama

get_copy_number_variant_info

Retrieve copy number variant information from gnomAD v4 database using CNV ID and reference genome to analyze genetic variations.

Instructions

[gnomAD API] Retrieve copy number variant info (v4 only) Args: reference_genome (str): Reference genome (GRCh38) variantId (str): CNV ID (e.g. 18714__DUP) Returns: dict: CNV info Note: Not supported in v2/v3.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
reference_genomeYes
variantIdYes
datasetNognomad_cnv_r4

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The tool 'get_copy_number_variant_info' is defined in server.py using the @mcp.tool() decorator. It validates the dataset and reference genome parameters before calling 'run_query_with_metadata' to fetch the CNV information from the gnomAD API.
    def get_copy_number_variant_info(
        reference_genome: str,
        variantId: str,
        dataset: str = 'gnomad_cnv_r4'
    ) -> dict:
        """
        [gnomAD API] Retrieve copy number variant info (v4 only)
        Args:
            reference_genome (str): Reference genome (GRCh38)
            variantId (str): CNV ID (e.g. 18714__DUP)
        Returns:
            dict: CNV info
        Note:
            Not supported in v2/v3.
        """
    
        if dataset != 'gnomad_cnv_r4':
            raise ValueError("Only v4 is supported for copy number variant info.")
        if reference_genome != 'GRCh38':
            raise ValueError("Only GRCh38 is supported for copy number variant info.")
    
        variables = {
            'dataset': dataset,
            'reference_genome': reference_genome,
            'variantId': variantId,
        }
        return run_query_with_metadata('copy_number_variant', variables)
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions the API source (gnomAD) and version constraints (v4 only), which adds some context. However, it lacks details on behavioral traits such as rate limits, authentication needs, error handling, or what specific info is returned (e.g., fields in the dict). For a tool with no annotations, this is a significant gap.

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 appropriately sized and front-loaded, starting with the core purpose. The use of sections (Args, Returns, Note) adds structure, but the note could be integrated more smoothly. There's minimal waste, though it could be slightly more polished.

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 no annotations, 0% schema coverage, and an output schema present, the description is moderately complete. It covers the purpose and some parameter semantics but lacks behavioral details and full parameter explanations. The output schema handles return values, so that gap is mitigated, but overall completeness is adequate with clear room for improvement.

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 provides examples for variantId (e.g., '18714__DUP') and specifies reference_genome as 'GRCh38,' adding meaning beyond the bare schema. However, it doesn't mention the dataset parameter or explain its purpose, leaving one of three parameters undocumented. This partial compensation results in a baseline score.

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 retrieves copy number variant info from the gnomAD API, specifying it's for v4 only. It distinguishes itself from siblings by focusing on CNVs rather than other variant types like ClinVar, mitochondrial, structural, or general variants. However, it doesn't explicitly contrast with get_structural_variant_info, which might be a close sibling.

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

Usage Guidelines3/5

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

The description implies usage by specifying 'v4 only' and noting 'Not supported in v2/v3,' which provides some context on when to use it. However, it doesn't explicitly state when to choose this tool over alternatives like get_structural_variant_info or get_variant_info, nor does it mention prerequisites or exclusions beyond version compatibility.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/koido/gnomad-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server