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ESG Hub MCP Server

Get Glossary Term

get_term
Read-onlyIdempotent

Look up one glossary term by record ID ('term:abc123'), permalink, or exact name and return its full definition and facets. Use it when the user asks 'what is '; to find terms by topic, or across all content, use search_esg or search_content, and to survey the glossary use list_terms. Name matching is exact (case-insensitive) with no fuzzy or partial matching, and it returns a single term, never a list. The definition field is the authoritative text and facets carries the topic/content_type classification; an unknown identifier returns NOT_FOUND. Cached ~10 minutes; rate-limited per IP; retry on 5xx.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
term_idYesTerm identifier — slug/name (e.g., 'materiality') or record ID (e.g., 'term:abc123')

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
termYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Beyond the readOnly/idempotent annotations, it discloses exact (case-insensitive) matching with no fuzzy/partial semantics, guarantees a single record rather than a list, specifies NOT_FOUND for unknown identifiers, and adds caching (~10 min), per-IP rate limiting, and 5xx retry guidance. These are operational traits an agent cannot derive from the annotations.

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?

Front-loads the core action, then alternates, then behavioral caveats, then operational notes. Every clause carries distinct information; nothing is restated from annotations or schema.

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?

An output schema exists, yet the description still orients the agent by naming the key fields (definition as authoritative, facets for classification). Identifier formats, failure mode, matching semantics, and rate-limit behavior are all covered, leaving no material gap for a single-parameter lookup.

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 coverage is 100% and the sole parameter is documented, so the baseline is 3; the description adds genuine meaning by enumerating permalink as an accepted form and stressing exact case-insensitive name matching, which the schema's 'slug/name or record ID' phrasing does not make explicit.

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?

States a specific verb (look up) and resource (glossary term), plus the accepted identifier forms and the return payload ('full definition and facets'). It also explicitly names the sibling tools it is not (search_esg, search_content, list_terms), so an agent can route without opening any schema.

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

Usage Guidelines5/5

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

Gives an explicit trigger ('what is <term>') and explicitly routes to alternatives for adjacent intents: search_esg/search_content for topical or cross-content lookup, list_terms for surveying the glossary. The when-not conditions are named alongside the tool that should be used instead.

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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