Genomics MCP

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describe_dataset

Read-only

Retrieve study or dataset details by native accession from EGA, ENA, ENCODE, GEO, or NCBI, including linked entities for structured metadata.

Instructions

Describe a study/dataset by native accession, with linked entities. Available for: ega, ena, encode, geo, ncbi_datasets.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`source`	Yes
`accession`	Yes

Output Schema

TableJSON Schema

Name	Required	Description	Default
`data`	No
`error`	No	Set when status is error.
`errors`	No	Per-source failures in partial results.
`limits`	No
`status`	Yes
`warnings`	No
`operation`	Yes
`provenance`	No
`truncation`	No
`source_status`	No
`schema_version`	No		1
`metadata_omitted`	No	Entries dropped from provenance/source_status/errors/warnings (or text shortened) to fit max_response_bytes. Absent when metadata is complete.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv0.1.1Sep 28, 2026

addedOutput schema / properties / metadata_omitted

Added value: +{
+  "anyOf": [
+    {
+      "additionalProperties": {
+        "type": "integer"
+      },
+      "type": "object"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "Entries dropped from provenance/source_status/errors/warnings (or text shortened) to fit max_response_bytes. Absent when metadata is complete.",
+  "title": "Metadata Omitted"
+}

First observedv0.1.0Sep 24, 2026

TDQS

A3.6/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety and network profile is covered. The description's 'with linked entities' adds useful scope about what the read returns. It does not mention auth requirements, source-specific rate limits, or resolution failures for invalid accessions, so it stays at an adequate 3.

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 short sentences with the purpose front-loaded and the source constraint immediately after. Nothing is wasted and nothing is buried.

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?

An output schema exists, so return-value shape needn't be described, and annotations cover read-only/open-world behavior. The source enumeration compensates for the missing schema descriptions. The main residual gap is accession format guidance, which is minor for a two-parameter read tool.

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 carry the semantics. It partially does: it enumerates the valid source values (ega, ena, encode, geo, ncbi_datasets) and clarifies that accession must be a 'native' accession. It says nothing about accepted accession formats or cross-source ID distinctions, so compensation is incomplete.

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?

Clear verb+resource: 'Describe a study/dataset by native accession, with linked entities.' The source list scopes what data it applies to, which helps separate it from search_datasets. However, it never explicitly contrasts itself with that sibling, so an agent must infer the difference between describing one dataset and searching many.

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 'Available for: ega, ena, encode, geo, ncbi_datasets' line acts as an applicability constraint, implying usage is limited to those sources. But there is no explicit when-to-use statement and no mention of search_datasets or resolve_identifier as alternatives for other cases, leaving routing to inference.

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