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ensembl-mcp-server

by io.github.cyanheads

Get Gene Homologs

ensembl_get_homology
Read-onlyIdempotent

Find orthologs and/or paralogs of a gene across species. Returns each homolog's stable ID, species, homology type (ortholog_one2one, ortholog_one2many, paralog_many2many, etc.), perc_id (percent identity), perc_pos (percent positives), and taxonomy level. Essential for cross-species research — for example, "what is the mouse equivalent of human TP53?" or "how conserved is BRCA2 across mammals?". Provide either symbol + species or a stable gene ID. Target species can be filtered to a single species or left open to return all available homologs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoEnsembl stable gene ID (e.g. ENSG00000139618). Use ensembl_lookup_gene to get the stable ID from a symbol. Cannot be combined with symbol.
typeNoType of homologs to return. orthologues: genes related by speciation (cross-species equivalents). paralogues: genes related by duplication (within or across species). all: both orthologs and paralogs.orthologues
symbolNoGene symbol in the source species (e.g. BRCA2, TP53). Species defaults to homo_sapiens; set species for other organisms. Cannot be combined with id.
speciesNoSource species (the species the query gene belongs to) in Ensembl internal format. Default is homo_sapiens. Use ensembl_list_species to discover valid values.homo_sapiens
max_resultsNoMaximum number of homologs to return. Broad orthology queries (e.g. BRCA2 across all species) can return 150+ homologs; the default keeps responses focused. Set to 0 to return every homolog uncapped. totalCount always reports the true number available before this cap.
target_speciesNoFilter to homologs in a single target species (e.g. mus_musculus for mouse). Omit to return homologs across all available species. Use ensembl_list_species to discover valid values.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
capNoThe max_results limit applied to the homolog list.
errorNoPresent when the call failed. Absent on success.
shownNoNumber of homologs returned after the max_results cap.
noticeNoGuidance when no homologs are found or the list was capped.
queryIdNoThe resolved Ensembl gene ID used for the homology query.
homologsNoHomologous genes found for the query gene, capped to max_results. totalCount reports the full count available before the cap.
queryTypeNoThe homology type queried (orthologues, paralogues, or all).
truncatedNoTrue when the homolog list was capped at max_results.
totalCountNoTotal number of homologs available before the max_results cap. Exceeds the returned homologs count when the list was capped.
querySpeciesNoThe source species used for the query.

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already establish readOnly, openWorld, and idempotent behavior. The description adds valuable behavioral substance by specifying exactly what kinds of data are returned, including homology type, percent identity, percent positives, and taxonomy level. This goes beyond the annotation bar and gives an agent a clear mental model of the output.

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?

The description is compact but information dense. Every sentence contributes something functional: the core purpose, return-value detail, motivation/examples, and input requirements. There is no filler or tautological phrasing.

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

Completeness5/5

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

For a tool of moderate complexity with five well-documented parameters, with annotations and an output schema already present, the description supplies all the missing operational context: when to use it, what kind of results to expect, and how to structure the query. Nothing essential for choosing or invoking it is left unexplained.

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 100%, so every parameter is already well documented. The description reinforces the id/symbol either-or constraint and the target-species filtering option, which adds a small amount of use-case framing but does not deepen the semantics of any parameter significantly. The schema remains the primary semantic source.

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?

The description opens with a specific verb and resource: 'Find orthologs and/or paralogs of a gene across species.' It clearly distinguishes from sibling tools like ensembl_get_sequence, ensembl_get_xrefs, and ensembl_lookup_gene by focusing specifically on cross-species homology relationships rather than sequences, annotations, or identifiers.

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?

It gives clear usage context with concrete examples ('what is the mouse equivalent of human TP53?') and states the two accepted input modes: symbol + species or stable gene ID. It also explains the target_species filtering behavior. However, it does not explicitly name sibling tools or say when not to use this tool, though schema-level guidance points to ensembl_lookup_gene for ID resolution.

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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TDQS

A4.5/5.0
Disambiguation5/5

Each tool targets a distinct genomic resource: homology, sequence, xrefs, species metadata, gene lookup, variant prediction, and region query. There is no overlap in their purposes, and the descriptions clearly delineate when to use each.

Naming Consistency5/5

All tool names follow the consistent pattern 'ensembl_' plus an action verb (get, list, lookup, predict, query) and a noun. The naming style is uniformly snake_case and lowercase, making the tool set predictable and easy to navigate.

Tool Count5/5

With 7 tools, the server is well-scoped for its purpose. Each tool addresses a core Ensembl query need without redundancy or bloat, fitting comfortably in the ideal range for a domain-specific toolkit.

Completeness5/5

The tool set covers the primary lifecycle of genomic investigation: discovering species, resolving gene identifiers, fetching sequences, obtaining cross-references, querying regions, finding homologs, and predicting variant consequences. There are no critical gaps for typical use cases.

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