plant-genomics-mcp

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KEGG Pathways

kegg_pathways

Read-onlyIdempotent

Fetches KEGG pathway memberships for a plant locus, returning pathway IDs, names, and categories. Supports Arabidopsis and major crops; pairs with locus_go_annotations for functional insights.

Instructions

Fetch KEGG pathway memberships for a plant locus from rest.kegg.jp. Returns a list of pathway IDs + names + KEGG category classes the locus participates in. Pairs with locus_go_annotations for the GO-level functional view. Covers: arabidopsis_thaliana, brachypodium_distachyon, glycine_max, hordeum_vulgare, oryza_sativa, populus_trichocarpa, zea_mays. Any other organism raises OrganismNotSupported before any request (both the single and batch forms). Non-Arabidopsis loci are bridged to the NCBI Entrez Gene ID KEGG indexes (returned as entrez_gene_id). A gene KEGG knows with no pathway memberships is an ok answer with pathways=[]; a gene KEGG has no record of raises NotFoundError. KEGG v118+ is case-sensitive on the locus: pass AGI loci as uppercase.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`locus`	Yes	Arabidopsis AGI locus, e.g. AT1G01010 (case preserved verbatim — KEGG v118+ is case-sensitive)
`organism`	No	Plant organism — accepts canonical slug, scientific or common name, or NCBI taxid; see the tool description for which KEGG covers	arabidopsis_thaliana

Output Schema

TableJSON Schema

Name	Required	Description
`locus`	Yes
`errors`	No	Per-pathway step-2 failures (kept inline so the call doesn't abort)
`organism`	Yes	Resolved canonical organism slug, e.g. arabidopsis_thaliana
`pathways`	Yes
`kegg_gene_id`	Yes	e.g. "ath:at1g01010"
`entrez_gene_id`	No	Entrez Gene ID from the non-Arabidopsis KEGG↔Entrez bridge; absent for ath.
`upstream_version`	No	KEGG release that produced THIS response, — always null today: this backend states no release on its responses; upstream_release(backend='kegg') reports the release its own endpoint calls current at query time, or why there is none. null means KEGG did not state one — never that no release exists, and never inferred from a separate metadata call, which can describe a different release than the one that answered.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv1.27.0Sep 27, 2026

changedOutput schema / properties / upstream_version / description

Previous value: -"KEGG release that produced THIS response, — always null today: this backend states no release on its responses. null means KEGG did not state one — never that no release exists, and never inferred from a separate metadata call, which can describe a different release than the one that answered."New value: +"KEGG release that produced THIS response, — always null today: this backend states no release on its responses; upstream_release(backend='kegg') reports the release its own endpoint calls current at query time, or why there is none. null means KEGG did not state one — never that no release exists, and never inferred from a separate metadata call, which can describe a different release than the one that answered."

Changed2 schema fields changedv1.22.0Sep 24, 2026

changedInput schema / properties / organism / description

Previous value: -"Plant organism — only arabidopsis_thaliana is supported in v1.1.0; other plants raise OrganismNotSupported until an Entrez bridge lands"New value: +"Plant organism — accepts canonical slug, scientific or common name, or NCBI taxid; see the tool description for which KEGG covers"

addedOutput schema / properties / upstream_version

Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "KEGG release that produced THIS response, — always null today: this backend states no release on its responses. null means KEGG did not state one — never that no release exists, and never inferred from a separate metadata call, which can describe a different release than the one that answered.",
+  "title": "Upstream Version"
+}

First observedv1.8.0May 30, 2026

TDQS

A4.2/5.0

Behavior5/5

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

Beyond the annotations (readOnlyHint, openWorldHint, idempotentHint, destructiveHint false), the description discloses several critical behaviors: OrganismNotSupported raised before any request for unsupported organisms, NotFoundError for genes KEGG has no record of, empty pathways list for genes with no memberships, case-sensitivity of KEGG v118+, and the bridging to NCBI Entrez Gene ID for non-Arabidopsis. These are valuable behavioral details that an agent needs to handle errors correctly.

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 dense but well-structured: it opens with the primary action and return format, then covers supported organisms, error cases, empty-result behavior, case sensitivity, and bridging. Every sentence carries distinct information with no filler. It is longer than a minimal description but each clause earns its place; the front-loading of the core function and return type helps an agent quickly understand the purpose.

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?

Given the tool's complexity (multiple organisms, error conditions, case sensitivity, bridging to Entrez IDs), the description is exceptionally complete. It explains return format (pathway IDs + names + categories, plus entrez_gene_id), error semantics (OrganismNotSupported, NotFoundError, empty list), supported organisms, and the case-sensitivity requirement. With an output schema present, the agent has everything needed to call and interpret results correctly without further inference.

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?

The input schema already provides 100% coverage with descriptions for both 'locus' (case preserved verbatim, case-sensitive) and 'organism' (accepts canonical slug, scientific/common name, or NCBI taxid). The tool description adds the list of supported organisms and the non-Arabidopsis bridging note, but these are more about behavior than parameter meaning. Since schema coverage is high, the description adds marginal extra semantic value beyond what the schema already states.

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 states a specific verb ('Fetch'), a resource ('KEGG pathway memberships') and the target ('a plant locus'), and immediately describes the return payload (pathway IDs, names, categories). It distinguishes itself from sibling tools like locus_go_annotations by mentioning it pairs with that tool, and its name clearly implies single-locus vs the batch sibling. No ambiguity about what the tool does.

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 provides context by noting it pairs with locus_go_annotations for the GO-level functional view, implying when this tool is useful. However, it does not explicitly state when to use this tool vs alternatives like batch_kegg_pathways (e.g., 'use this for a single locus, use batch for multiple'), nor does it state when NOT to use it. The guidance is implied rather than explicit.

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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