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whitney-museum-mcp-server

Raw Whitney API query

whitney_query
Read-onlyIdempotent

Query any Whitney Museum API endpoint with raw Ransack predicates, filters, sorting, pagination, or by ID. Use for custom searches, field discovery, or reaching the pages endpoint.

Instructions

Escape hatch for queries the typed tools do not cover. Hits any endpoint with arbitrary Ransack predicates.

Args:

  • endpoint ('artists' | 'artworks' | 'exhibitions' | 'events' | 'guides' | 'pages')

  • id (string, optional): fetch a single record instead of a list

  • filters (object, optional): raw predicates, e.g. { "medium_cont_all_split": "graphite paper" }

  • sort (string, optional): e.g. 'popularity desc'

  • page (number, default 1), limit (number, 1-30, default 10)

  • response_format ('markdown' | 'json', default 'markdown')

Returns: a list result, or { record: {...} } when 'id' is supplied.

Prefer the typed tools where they fit — they return tidier records. Use this to discover field names, combine unusual predicates, or reach the 'pages' endpoint. Note that 'pages' mirrors the Museum's CMS structure and is rarely useful outside it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoFetch one record by ID instead of listing
pageNo1-based page number; the API returns 30 records per page
sortNoRansack sort string
limitNoMaximum records to return from the fetched page (1-30). Keep this low unless you need the detail — Whitney records are verbose.
filtersNoRaw Ransack predicates, e.g. { "title_cont": "moon", "classification_eq": "Paintings" }. Matchers: _eq, _not_eq, _cont, _not_cont, _cont_all_split, _true, _false, _gt, _gteq, _lt, _lteq.
endpointYesWhich API endpoint to query
response_formatNoOutput format: 'markdown' for reading, 'json' for machine processingmarkdown

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already declare read-only, idempotent, non-destructive behavior, and the description adds meaningful context: it returns a list or a single-record object when 'id' is supplied, accepts raw predicates, and warns that 'pages' mirrors the Museum's CMS structure and is rarely useful. This goes well beyond the structured fields.

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?

The description is well-organized: a one-line purpose statement, a compact Args list, return behavior, and usage guidance. Every sentence earns its place, and the most important scoping information is front-loaded.

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 raw query tool with no output schema, the description provides enough to call it correctly: endpoint options, parameter roles, default values, return shape, and guidance on when to use alternatives. The absence of output schema is compensated by the explicit 'Returns' line.

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 met; the description adds value with a sort example ('popularity desc'), a filters example with a real predicate, and a compact summary of endpoint, id, limit, and response_format semantics. It mostly restates the schema, but the examples and use-case framing give extra orientation.

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 clearly identifies this as an 'escape hatch' for queries the typed tools do not cover, with a specific verb ('Hits') and resource (any of six named API endpoints). It also distinguishes itself from the typed sibling tools by promising arbitrary Ransack predicates and raw API access.

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?

It explicitly says to 'prefer the typed tools where they fit' and names concrete scenarios for using this tool: discovering field names, combining unusual predicates, and reaching the 'pages' endpoint. The 'pages' caveat also tells the agent when the endpoint is not useful.

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