Wallector
Description
Wallector helps you explore, understand, and navigate the world of fine art and collectibles. Access curated knowledge, expert insights, and market-focused content designed for collectors, enthusiasts, and professionals looking to make informed decisions in the art and collectibles space.
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Capabilities
Publisher Intelligence
Insights and recommendations for app publishers. See how your app performs and how to improve discoverability.
Server Status wallector-mcp v0.2.10
https://mcp.wallector.com/mcp Last checked: 1d ago
Technical Details
Tools(3)
Showing 3 of 3 tools
| Tool | Description | Flags | Test | Last Tested | |
|---|---|---|---|---|---|
detail_listings | Return detailed information for a single artwork by exact SKU. This tool is a constrained works search (intent="works", limit=1, offset=0) with a required SKU filter; it never groups results and always renders the detail widget. | read-only | 100%Latency 4.2s | May 9, 2026 | |
get_capabilities | Return supported tools, listing fields, filters, grouping, and known API gaps for this MCP server. Use ONLY if the user explicitly asks about capabilities, schema, limits, or supported fields. | read-only | 100%Latency 66ms | May 9, 2026 | |
search_listings_v2 | Search listings with intent (groups|works), pagination, and sorting. Use intent=groups with group_by on canonical groupable fields that are available for this source: work_group, artist_name, category, typology, technique, topics, subjects, style_tags, movement_period, seller.seller_name. Use intent=works for SKU-level works. Filters: sku, work_group, title, artist_name, category, typology, seller_name, topics, subjects, style_tags, movement_period, period, materials, technique, q. Range filters: min_price|max_price, min_height|max_height, min_width|max_width, min_depth|max_depth, min_quantity|max_quantity. Image/semantic inputs for works: image (file param object with download_url,file_id), image_url, image_base64, q with search_mode=semantic|hybrid. Semantic modes are supported via search_mode=lexical|hybrid|semantic. For natural-language requests (example: "mostrami quadri con cavalli"), prefer q with search_mode=hybrid and combine with canonical filters when present (example typology/category). Use lexical when the request is exact (SKU, strict keyword match), semantic when lexical misses concept matches, and hybrid as default when available. Pagination is explicit: use group_limit/group_offset for groups and limit/offset for works. IMPORTANT: for "works by artist" requests, make one works call directly (artist_name) and do not preflight with groups. | read-only | 100%Latency 91ms | May 9, 2026 |
Discoverability Score
Fair
52 of 100 — how easily AI agents find your app
- Description quality20/20
- Example prompts0/20
- Keyword coverage0/15
- Tool metadata16/20
- Visual assets5/20
- Endpoint health10/10
- Data freshness11/15
How to Improve
Add at least 2 example prompts. Prompt examples strongly improve app matching and click-through intent.
Increase keyword coverage (discovery + trigger) to improve retrieval for long-tail queries.
Provide a stable HTTPS logo URL (avoid connectors://) so cards render consistently across clients.
Add at least 2 screenshots that show real workflows to increase confidence and conversion.
Technical Details
- Status
- ENABLED
- Type
- AI-Powered App
- Auth
- Open Access
- Listed on
- ChatGPT
- Added
- January 11, 2026
- Last synced
- May 3, 2026
- Last checked
- 1d ago
- Version
- 0.2.10
- Distribution
- Ecosystem Directory