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Exposes the Dictionary of Applied Machine Learning (https://dictionaryofml.org) to AI assistants via the Model Context Protocol: look up a term, search the definitions, walk the cross-reference graph.
Four read-only tools with basic descriptions and schemas. Tool names follow verb_noun convention (list_, lookup_, search_, get_). Descriptions are present but minimal (34 - 72 chars, below the 50 - 200 char LLM-optimized baseline). Input schemas are defined with proper JSON Schema, but parameter descriptions are entirely absent, LLMs cannot infer what 'term' or 'query' mean without explicit guidance. No output schema documentation. Error handling is minimal (generic 'No term matching' messages). No pagination support despite search_terms potentially returning many results. Overall: functional but well below production quality.
The terms a given entry cross-references (its See-also list), with their abstracts.
List every term of the Dictionary of Applied Machine Learning (name and key).
Full dictionary entry (abstract, definition, cross-references) for a term, by key or name.
Search term names and definitions for a keyword or phrase; returns the best matches.
No parameter descriptions. 'term', 'query', and 'limit' parameters lack any guidance on expected format, constraints, or examples. LLMs cannot infer whether 'term' accepts a key, display name, or both.
No output schema documentation. Callers cannot predict the structure of returned text or plan downstream operations. Tool descriptions do not specify what fields or format to expect.
search_terms lacks pagination. No limit default, no offset/cursor, no total count. Returning all matches could exhaust context window; no guidance on result capping.
Minimal error recovery guidance. 'No term matching X' does not suggest alternatives or next steps. LLMs cannot self-correct without explicit recovery hints.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | D | 57 | 2026-07-28+ | v2 |
Tool descriptions are too brief (34 - 72 chars vs. 50 - 200 char baseline). Lack context on WHEN to use each tool and how they differ. 'Full dictionary entry' vs 'Search term names' distinction is unclear.