Skip to main content
Glama
berntpopp
by berntpopp

Get Meta-Domain Variants

get_meta_domain
Read-onlyIdempotent

Retrieve homologous variant evidence for a protein residue, combining gnomAD normal variants and ClinVar pathogenic variants across conserved Pfam domain families.

Instructions

Return homologous (meta-domain) variant evidence for one residue: gnomAD normal_variants and ClinVar pathogenic_variants observed at the aligned consensus position across the residue's Pfam domain family, each carrying its homolog gene_name. Omit domains to derive the selector from the residue's cached domain mapping; a residue with no meta-domain returns empty lists (not an error). Requires a built landscape. Signature: get_meta_domain(transcript_id=, position=, domains=, limit=, offset=, response_mode=).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum rows to return (1..1000; default 200).
offsetNoZero-based offset into the result list (for paging).
domainsNoOptional meta-domain selector {PfamID: [consensus_pos, ...]}. Omit to derive it from the residue's cached domain mapping.
positionYes1-based protein residue position.
response_modeNoVerbosity: minimal|compact|standard|full (default compact).compact
transcript_idYesA versioned Ensembl transcript id (the .N version suffix is required), e.g. ENST00000269305.4. Resolve a gene symbol with resolve_transcript first.
Behavior5/5

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

Annotations (readOnlyHint, idempotentHint, non-destructive) are consistent. Description adds key behavioral details: returns empty lists for missing meta-domain (not an error), requires built landscape, and includes homolog gene_name in output. No contradictions.

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

Conciseness5/5

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

Single well-structured paragraph. Begins with core action, then explains behavior, then gives signature. Every sentence adds meaningful information. No repetition or fluff.

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

Completeness4/5

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

Given 6 parameters, no output schema, and annotations present, the description explains return type, error handling, input derivation, and requirement. Lacks explicit pagination description but limit/offset are in schema. Sufficient for an AI agent to use correctly.

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

Parameters4/5

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

Schema description coverage is 100%, but description adds extra meaning: clarifies 'homologous' and 'aligned consensus position' for position parameter, explains derivation behavior for domains parameter. Provides value beyond schema, especially for domains and response_mode.

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

Purpose5/5

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

Description clearly states it returns homologous variant evidence for a residue, specifying data sources (gnomAD, ClinVar) and fields (homolog gene_name). Contrasts with omitting domains to auto-derive from cached mapping. Distinguishes from sibling tools like get_position_tolerance and get_variant_counts.

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

Usage Guidelines4/5

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

Provides explicit usage context: requires built landscape, empty lists for no meta-domain, option to omit domains for auto-derivation. Does not explicitly compare to alternatives among siblings or state when not to use, but the context is sufficient for an AI agent to decide.

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/berntpopp/metadome-link'

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