Art provenance intelligence — 282K-node knowledge graph with cited answers and honest gaps.
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Scored across 27 tools
Each tool targets a distinct action and resource type: get_* for entity retrieval, search_* for list discovery, query_* for analytical views, lookup_* for external sources, and find_* for specialized discovery. Descriptions explicitly warn against using the wrong tool (e.g., 'Do NOT use when' statements), making selection unambiguous.
Overall pattern is verb_noun with semantic verbs (get, search, query, lookup, find) that align with operation types. Minor inconsistencies exist: bare 'search' and 'fetch' wrappers, and 'byok_external_query' uses an acronym and noun-like structure. These are small deviations in an otherwise systematic naming scheme.
At 27 tools, it's slightly above the ideal 3-15 range, but the server's purpose is a comprehensive art-intelligence platform covering provenance, market, exhibitions, external lookups, and analytics. Each tool earns its place, and the count is justifiable given the domain breadth.
The tool surface is remarkably complete for a read-only intelligence platform: entity retrieval (artist, artwork, gallery), discovery (search, find), career analysis, provenance, reception, market aggregates, external museum lookups, and custom BYOK endpoints. No obvious dead ends; even sparse data scenarios return actionable guidance.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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Provenance-tagged knowledge graph of AI/ML research: papers, citations, methods, code.
AI-native art catalogue. Catalogue works, parse provenance, and generate signed RAIs.
NVIDIA AI knowledge graphs — 20 domains. 4x F1, 11x fewer tokens, SHA-256 provenance. MCP-native.
Deterministic knowledge for AI agents: search, fetch, cite and verify a 48M-entry knowledge base.
Add one secure layer between your agents and this server.
