Colour Memory

Archive Keyword Search

archive_search

Read-only

Full-text keyword search across all archive colour names and notes. Find colours by name fragment, material, cultural reference, pigment type, or historical period. Complements conceptual embedding search with exact keyword matching. Examples: 'cerulean' (28 matches, e.g. Bourton Cerulean), 'Prussian' (187 matches spanning pigment history), 'medieval' (over 1,000 matches across period archives). Never returns a bare empty result for a genuinely obscure query -- result_path in the response is 'direct' (exact keyword hit), 'broadened' (archive restriction dropped), or 'redirected' (fell back to conceptual/semantic search) so you always know which one fired. Set entity_mode='exact' to search by botanical identity rather than by word: a plain query for 'Rose' matches any cultivar name containing it (including Sweet Peas called 'Rose Pink'), whereas entity_mode='exact' returns genus Rosa only and discloses how many off-genus records were excluded.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No	Alias for n_results
`query`	Yes	Search term e.g. cerulean, Prussian, Ottoman, ochre, medieval
`offset`	No	Skip this many ranked matches before returning results -- collection paging. The response's next_offset gives the value to pass here for the next page; it is absent on the last page. total_found always reports the full collection size.
`archive`	No	Optional archive filter e.g. oxfordshire, japan, pigment, keats, eic, racingsilks
`year_to`	No	Boost entries on or before this year e.g. 1600 for Renaissance, 1901 for Victorian
`n_results`	No	Results per page (default 10, max 50 per call). This is a PAGE size, not a collection limit -- for a large collection (tens or hundreds of records) page with offset until next_offset disappears, and never tell the user the product caps out at one page.
`year_from`	No	Boost entries on or after this year e.g. 1400 for Renaissance, 1837 for Victorian
`entity_mode`	No	'text' (default): ordinary keyword search -- 'rose' finds any name containing the word, across genera. 'exact': resolve the query to a botanical entity and return ONLY records whose structured identity matches. Use 'exact' when you mean the plant, not the word: entity_mode='exact' with query='Rose' returns genus Rosa only and excludes Sweet Pea cultivars named 'Rose Pink'. The response carries an entity_resolution block showing the resolved genus and how many off-genus rows were excluded.	text
`include_full`	No	Return complete notes and source fields. Default false returns 150-char snippets. Set true for report workflows.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A4.8/5.0

Behavior5/5

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

Annotations only declare readOnlyHint=true; the description adds substantial behavioral detail beyond that: never returns a bare empty result, result_path values ('direct', 'broadened', 'redirected'), the archive-restriction drop, semantic fallback, and entity-resolution exclusion disclosure. No contradiction with readOnly.

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?

Three dense, front-loaded paragraphs; purpose and scope appear first, followed by behavioral guarantees and entity-mode semantics. Examples and paging warnings justify their length, and no sentence is wasted.

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 9-parameter search surface, output schema, and read-only annotation, the description covers what the tool searches, result interpretation, pagination semantics, entity-mode distinction, and fallback behavior. Nothing an agent needs to invoke it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema covers 100% of parameters, so baseline is 3, but the description adds critical semantics: n_results is a page size not a collection cap, offset paging via next_offset, entity_mode='exact' exclusion behavior, and concrete query examples with match counts. This materially exceeds the schema.

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?

Description opens with a specific verb and scope: 'Full-text keyword search across all archive colour names and notes' and enumerates search dimensions (name fragment, material, cultural reference, pigment type, historical period). It explicitly contrasts with conceptual embedding search, distinguishing it from sibling query_conceptual.

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?

Clear context: use for exact keyword matching when conceptual embedding search is not appropriate, and use entity_mode='exact' when the query means a botanical entity. It does not enumerate other archive_* siblings or state explicit when-not-to-use rules, so not a full 5.

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

All Colour Memory tools Inspect

Try in Browser

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.8/5.0

Disambiguation2/5

With 88 tools, there is substantial overlap: colour_passport vs colour_dna vs colour_metrics vs colour_cultural_risk are explicit components of the same object; palette_concept vs palette_strict vs palette_generate vs palette_heritage overlap heavily; and four image extraction tools exist (extract_image_colours, image_palette, palette_extact, ingest_image). Although descriptions are detailed and tool_guide exists, an agent will frequently struggle to select the correct tool unambiguously.

Naming Consistency5/5

Nearly all tools follow a consistent snake_case noun_verb or domain-prefixed pattern (colour_*, palette_*, brand_*, archive_*, project_*, accessibility_*). The naming is uniform and predictable, with no mixing of styles or verb conventions across the set.

Tool Count1/5

88 tools is an extreme count for an MCP server. Even honoring the broad domain, the rubric places 50+ at the extreme end, and the high overlap between compound and individual tools suggests many could be consolidated or exposed as sub-resources rather than top-level tools.

Completeness5/5

The tool surface covers the full colour lifecycle: lookup, analysis, palettes, brand systems, accessibility, image extraction, interior design, archival research, reports, PDF generation, and project management. Workflows have clear entry points and few dead ends, and the presence of compound tools further closes integration gaps.

Resources

Need Help?