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musharna

plant-genomics-mcp

get_gene_xrefs

Retrieve cross-database references (UniProt, NCBI Gene, TAIR, etc.) for a plant locus from Ensembl Plants. Returns count, raw list, and by-database rollup for fast identifier lookup.

Instructions

Fetch cross-database references (UniProt, NCBI Gene, TAIR, ArrayExpress, …) for a plant locus from Ensembl Plants. Defaults to arabidopsis_thaliana; pass organism= for other Ensembl Plants species. Returns count + raw xref list + a by_db rollup keyed on Ensembl's dbname (e.g. 'Uniprot_gn', 'EntrezGene') for fast lookup of a single foreign identifier.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
locusYese.g. AT1G01010 (Arabidopsis), Os01g0100100 (rice)
organismNoPlant organism — accepts canonical slug (arabidopsis_thaliana), scientific or common name, or NCBI taxidarabidopsis_thaliana

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
locusYes
organismYes
countYesNumber of xref records returned
xrefsYesRaw Ensembl xref records
by_dbYesdbname → primary_ids[]; e.g. {'Uniprot_gn': ['Q0WV96']}
Behavior4/5

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

Since no annotations exist, the description carries full burden. It discloses the return structure (count, raw xref list, by_db rollup) and key naming, which is valuable. However, it omits details like rate limits, authentication needs, or error handling.

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?

Two sentences, each efficient: first states purpose and examples, second adds default and return structure. No wasted words, front-loaded with key information.

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?

Completeness is high for a lookup tool with 2 params and output schema: purpose, parameter hints, and return structure are covered. Lacks error handling or fallback details, but overall sufficient for correct usage.

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 coverage is 100% with adequate descriptions for both parameters. The description adds minimal new information (restating default organism and that organism= can be passed), which is not significantly beyond the schema.

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 fetches cross-database references for a plant locus from Ensembl Plants, listing example databases. It is specific about the resource and action, but does not explicitly differentiate from sibling tools like ensembl_plants_lookup_locus, which may have overlapping scope.

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?

The description provides parameter guidance by noting the default organism and how to change it, but lacks any indication of when to use this tool versus siblings (e.g., batch_get_gene_xrefs) or when not to use it. No explicit usage context is given.

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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