art-institute-chicago-mcp-server

Search artworks

artic_search_artworks

Read-onlyIdempotent

Search the Art Institute of Chicago collection by text and structured filters, ranked by relevance or sorted by date. Text matches all words across titles, artists, descriptions, provenance, and other catalog fields. Filters combine with AND. Results reach the first 1,000 matches; narrow with filters for more. Set limit to 0 with facets to get only counts. Use artic_lookup_vocabulary for filter values and artic_get_artworks for full records.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`page`	No	Page to return (1-based); page times limit may not exceed 1,000.
`sort`	No	relevance ranks by query text, or by museum popularity without it; date_asc and date_desc sort by start year.	relevance
`limit`	No	Rows per page (0-12; capped so a page of long catalog records with every facet stays within common tool-output limits); 0 returns only totalCount and facets.
`query`	No	Text matched against titles, artists, descriptions, provenance, and other catalog fields; every word must match. Supports "exact phrase", -exclude, and a \| b.
`style`	No	Style title as artic_lookup_vocabulary lists it (case ignored), such as Impressionism; matches preferred or alternate styles.
`theme`	No	Theme title as artic_lookup_vocabulary lists it (case ignored), such as Women artists.
`artist`	No	Artist or culture name matched against every credited artist (all words must match).
`facets`	No	Facet counts to compute over the filtered set (top 15 values each): department, artwork_type, style, subject, classification, place_of_origin, artist. An array or a comma-separated string.
`gallery`	No	Gallery where the work is on view, such as Gallery 240 (a bare 240 is read as Gallery 240). Only on-view works carry a gallery.
`subject`	No	Subject title as artic_lookup_vocabulary lists it (case ignored).
`year_to`	No	Latest year; a work matches when its date span overlaps year_from to year_to. Negative for BCE.
`material`	No	Material title as artic_lookup_vocabulary lists it (case ignored), such as ink or gold leaf.
`artist_id`	No	Agent id from artic_search_artists or an artist facet row; matches preferred and other credits.
`has_image`	No	Only works with an image.
`technique`	No	Technique title as artic_lookup_vocabulary lists it (case ignored), such as black-and-white photography or plain weaving.
`year_from`	No	Earliest year; a work matches when its date span overlaps year_from to year_to. Negative for BCE.
`department`	No	Department title exactly as artic_lookup_vocabulary lists it (case ignored), such as Prints and Drawings.
`artwork_type`	No	Artwork type title as artic_lookup_vocabulary lists it (case ignored), such as Painting or Print.
`on_view_only`	No	Only works on view at the museum now.
`classification`	No	Classification title as artic_lookup_vocabulary lists it (case ignored), such as oil on canvas or etching.
`place_of_origin`	No	Place of origin as artic_lookup_vocabulary lists it (case ignored), such as france.
`public_domain_only`	No	Only public-domain works, whose images are CC0.

Output Schema

TableJSON Schema

Name	Required	Description
`cap`	No	The limit applied to this page.
`page`	No	Page returned (1-based).
`error`	No	Present when the call failed. Absent on success.
`shown`	No	Rows returned on this page.
`facets`	No	Counts over the filtered set for each requested facet; present only when facets were requested.
`notice`	No	Guidance when nothing matched, more pages exist, or the reachable window is exhausted.
`artworks`	No	Matching artworks on this page, in ranked or sorted order.
`has_more`	No	True when more matches exist beyond this page.
`next_page`	No	Page to request next; absent when nothing remains or the next page would pass the first 1,000 matches.
`truncated`	No	True when more matches exist beyond this page.
`totalCount`	No	Matches for the query and filters, before paging.
`license_text`	No	License statement from the API for this data, verbatim.
`sort_applied`	No	Order applied; popularity when relevance was requested without query text (the museum popularity ranking).

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 2, 2026

TDQS

A4.7/5.0

Behavior4/5

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

Annotations already declare readOnly, openWorld, and idempotent, so the safety profile is covered. The description still adds real behavioral facts not in the annotations: the 1,000-result cap, AND-combination of filters, and the limit=0 + facets counting behavior. Only return-shape details are left to the output schema.

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?

Four tightly packed sentences, front-loaded with the core purpose before the routing and pagination caveats. No filler and every sentence conveys a distinct, usable fact.

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?

For a 22-parameter search tool with an output schema and rich annotations, the description supplies the routing, cap, AND-combination, and facet-count behavior an agent needs. Return values are correctly left to the output schema.

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%, so the baseline is 3 without further value. The description earns above baseline by disclosing cross-parameter semantics the schema states only per-field: that filters combine with AND, that text matches across all catalog fields, and that page×limit must stay under 1,000.

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 first sentence states a specific verb (Search) and resource (Art Institute of Chicago collection) plus the scope (text and structured filters, ranked or sorted). It is unmistakably distinct from siblings like artic_search_artists or artic_search_exhibitions.

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?

Explicitly routes the agent: use artic_lookup_vocabulary for filter values and artic_get_artworks for full records. It also gives an actionable fallback when the 1,000-match ceiling is hit (narrow with filters) and a special-case pattern (limit 0 with facets for counts only).

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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