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R3PLICA AI Connector MCP Server

answering

R3PLICA AI Connector is answering right now. Last checked 4 min ago. 54 installs a week from npm. It exposes 16 tools.

Catalog of certified digital replicas from premium design brands, for any MCP-compatible AI agent.

The linked repository no longer exists on GitHub — it was deleted or made private.

Installs per day peak 18 · avg 5 · -20% w/w
a month agotoday
Uptime history 91 days of history · worst day 49%
91 days agonow
50.0%
Uptime 24h
91 of 182 checks
16
Tools
read from the server
140 ms
Response time
average over 24h
54
Installs / week
npm and PyPI

R3PLICA AI Connector does not always answer

Over the last week it answered 49.9% of our checks. We check every 15 minutes, so you hear about the next outage within the hour — not from your users.

Three servers free · no card

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 4 min ago.

run in your terminal
claude mcp add catalog --transport http https://mcp.r3plica.space/mcp
Settings → Connectors → Add custom connector, then paste this address
https://mcp.r3plica.space/mcp
~/.codex/config.toml
[mcp_servers.catalog]
url = "https://mcp.r3plica.space/mcp"
.cursor/mcp.json
{
  "mcpServers": {
    "catalog": {
      "url": "https://mcp.r3plica.space/mcp"
    }
  }
}
.vscode/mcp.json
{
  "servers": {
    "catalog": {
      "type": "http",
      "url": "https://mcp.r3plica.space/mcp"
    }
  }
}

This endpoint answered with an authorization challenge. The server is running, and it signs you in through your browser: there is no API key to paste.

This server publishes 1 more address. The block above uses the one we reach during checks; the full list is under Endpoints below, and the author may intend a particular one for your client.

Available tools 16

Read directly from the server with tools/list, grouped by what they act on. If a tool disappears, we record the date.

product
product_collection_list
List product collections (a brand's product lines, e.g. 'Eclipse', 'Charisma'). Default limit 100. A product collection is a named product line within a brand — NOT a finish set (use finish_collection_* for those). Triggers: 'what collections does <brand> have', 'list <brand> product lines', 'quali collezioni ha <brand>', 'le linee di <brand>'.
product_collection_search
Search product collections by name substring (product lines, not finish sets). Triggers: 'find the <x> collection', 'cerca la collezione <x>', 'la linea <x>'.
product_compare
Compare two products side by side. Returns two markdown cards under `## Product 1` / `## Product 2`, each with a 2-column spec table. Triggers: 'compare X and Y', 'X vs Y', 'which is bigger/better', 'differenza tra X e Y', 'confronta X e Y', 'meglio X o Y'. CRITICAL: preserve both card structures verbatim — the side-by-side tables are how the user visually compares.
product_get
Get detailed information about a specific product. Returns one structured markdown card (heading + `![](thumbnail_url)` image + spec table + description + catalog link). CRITICAL: preserve the markdown image and table verbatim. Do not flatten into prose. Do NOT reconstruct the thumbnail URL from asset_name — copy the provided `![](url)` line as-is.
product_list
List R3PLICA products with optional structured filters (brand, category, collection, designer, year). Use this for browsing/filtering by attribute (e.g. 'all Cassina sofas', 'chairs from 2020'); use product_search instead when the user gives a free-text query or keyword. Triggers: 'show me <category>', 'list <brand> products', 'browse the catalog', 'mostrami <categoria>', 'fammi vedere i prodotti di <brand>', 'sfoglia il catalogo'. Default limit is 50 products per call — raise via the `limit` argument if needed. Returns a sequence of structured markdown product cards: each has a `###` heading with name and brand, an inline `![](thumbnail_url)` markdown image, a 2-column markdown table with the spec rows (Designer, Year, Collection, Dimensions, Materials, Category), a blockquote description, and a catalog deep-link. CRITICAL when replying to the user: emit the cards VERBATIM as returned. Keep every `###` heading, the full markdown image line, the markdown table (`| ... |`), the blockquote, and the `[View on R3PLICA catalog →](url)` link untouched. Do NOT flatten the table into a comma-separated paragraph. Do NOT rewrite specs as prose. Do NOT construct alternate URLs from the asset_name — the CDN prefix is `SM_` (Static Mesh) for all products regardless of brand; pattern-matching brand-derived prefixes produces broken links.
product_search
Search R3PLICA products by free-text query. Returns structured markdown product cards (heading + thumbnail image + spec table + description + catalog link). Use this when the user gives a keyword or descriptive phrase (e.g. 'find a curved velvet sofa', 'lounge chairs'); use product_list when filtering purely by structured attributes. Triggers: 'find <x>', 'search for <x>', 'do you have <x>', 'I'm looking for <x>', 'cerca <x>', 'trova <x>', 'avete <x>', 'sto cercando <x>'. Default limit is 50. CRITICAL: preserve the markdown structure verbatim — keep the `![](url)` image lines and the tables, do not flatten into prose. NEVER reconstruct image URLs from asset_name yourself — the CDN file prefix is constant (`SM_`), not brand-derived.
product_stats
Catalog statistics grouped by category, brand, designer or year. Returns aggregate counts only — small, fixed-size payload. Triggers: 'how many products', 'catalog breakdown', 'how many sofas/chairs', 'products per brand', 'quanti prodotti', 'quanti per brand', 'statistiche catalogo', 'quante sedie avete'.
finish
finish_collection_get
Get a finish collection detail with all its individual finishes. Response includes `catalog_url` (deep-link to the collection page on catalog.r3plica.space), `finish_directory[]` (compact flat list with name + mongo_id + asset_name + thumbnail_url — designed to survive context truncation), and `finish_details[]` (full nested data). CRITICAL when generating documents/artifacts: copy the `thumbnail_url` and `catalog_url` fields VERBATIM. Do NOT construct catalog URLs yourself — the route is `/go/finish/<mongo_id>` (singular 'finish', NOT 'finish-collection' or 'finish/collection'). Do NOT construct thumbnail URLs from asset_name. If you need data for a single finish whose parent collection has been pushed out of context, call `finish_get` instead.
finish_collection_list
List R3PLICA finish collections (e.g. fabric, leather, wood, marble, metal sets sold as one asset). Optional brand/category filters. Default limit 5 collections per call — each can contain 30-50 individual finishes once enriched, so keep limits modest. TERMINOLOGY: a `finish_collection` is the asset sold on the platform; it contains many individual `finishes` inside `finish_details[]`. Do NOT call individual finishes 'variants' — 'variant' is reserved for product dimensional/additional variants. Response shape: { _meta: { terminology, asset_paths, deep_link_routes, thumbnail_rule, catalog_url_rule }, data: [collections] }. Each collection has a `catalog_url` and a flat `finish_directory[]`; each finish in `finish_details[]` carries a `thumbnail_url`. CRITICAL when embedding images: use the `thumbnail_url` field VERBATIM. NEVER construct CDN URLs from `asset_name` yourself — the file prefix is `MI_` (Material Instance) for ALL finishes regardless of brand; agents that infer brand-derived prefixes like `MO_`/`BO_` produce broken links.
finish_collection_search
Search finish collections by name. Default limit 10. Response includes `_meta.terminology` + `_meta.asset_paths` notes and each finish in `finish_details[]` carries a `thumbnail_url`. CRITICAL: never construct CDN URLs from asset_name yourself — use the `thumbnail_url` field as-is.
finish_get
Look up a single individual finish by its mongo_id. Returns its exact `name` (e.g. 'Saffron', 'Walnut'), `asset_name`, `thumbnail_url`, `catalog_url` (deep-link to the PARENT collection page — individual finishes don't have their own page), and parent finish collection identity. Use this when composing documents and you need the precise URL for a specific finish without re-fetching the whole collection — avoids the URL-guessing trap when the collection has already been pushed out of your context window.
finish_search
Search individual finishes across all collections by finish name (e.g. 'Walnut', 'Saffron') or asset_name substring. Optional `collection` filter narrows by finish collection name. Default limit 50. Returns each match with `asset_name`, `thumbnail_url`, and parent collection identity attached. Use when you know the finish name but not its mongo_id — e.g. 'find me the Walnut finish in the Bolzan Wood collection'.
brand
brand_get
Detailed information about a specific brand by name (description, country, designers, catalog presence). Triggers: 'tell me about <brand>', 'info on <brand>', 'who is <brand>', 'parlami di <brand>', 'chi è <brand>'.
brand_list
List all R3PLICA partner brands (default limit 200). Triggers: 'what brands do you have', 'list the brands', 'which brands are on R3PLICA', 'quali brand avete', 'elenca i brand', 'che marche ci sono'.
brand_search
Search R3PLICA brands by name substring. Use when the user mentions a brand but you need to resolve the exact catalog name. Triggers: 'find the brand <x>', 'is <x> on R3PLICA', 'cerca il brand <x>', 'avete <x>'.
style
style_guide_get
Return the R3PLICA brand and output style guide as markdown. Covers card structure, typography, color palette, image aspect ratio (always square), hierarchy, mandatory link footer, and ready-to-copy empty card scaffolds (product card, finish swatch, both markdown and HTML). CALL THIS FIRST whenever you are about to generate any document, report, artifact or branded output about R3PLICA catalog content. The guide ensures outputs feel consistent across users and align with the platform's visual identity. Costs ~2KB of context but saves the conversation from inconsistent formatting and from inventing fields the platform doesn't expose (prices, lead times, certifications).

Endpoints

URLTransportStateLatencyChecked
https://mcp.r3plica.space/mcp streamable-http sign-in 110 ms 4 min ago
https://mcp.r3plica.space/sse sse answering 100 ms 4 min ago

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R3PLICA AI Connector — questions

Answers built from our own checks of this server.

What can R3PLICA AI Connector do?
It exposes 16 tools, read directly from the server on our last check. Among them: brand_get, brand_list, brand_search, finish_collection_get, finish_collection_list, finish_collection_search and 10 more. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README. How MCP servers expose tools in the first place →
What is R3PLICA AI Connector mostly used for?
Its tools cluster around product, finish and brand. That is what this server is built to work with — the grouping comes from the actual tool names, not from a category we assigned.
Is R3PLICA AI Connector working right now?
We send a real MCP handshake every 15 minutes. Over the last 24 hours 91 of 182 checks got a reply (50.0%), average response time 140 ms. The bar chart above shows every period we have measured.
Is R3PLICA AI Connector still maintained?
The linked repository no longer exists on GitHub — it was deleted or made private. We show this because it changes what you can expect: an unmaintained server may keep answering for months and then stop without warning.
How do I connect R3PLICA AI Connector?
Copy the ready config from this page. We generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each in the form that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address. You sign in through your browser once and the client keeps the session: no key to copy, and it refuses anonymous clients.
How do you sign in to R3PLICA AI Connector?
No API key is involved. R3PLICA AI Connector answers our knock with an OAuth challenge, so you authorise it once in your browser and the client keeps the session. That is also why we see no tool list: it will not describe itself to an anonymous client, and that is the server working as intended, not a fault.
How fast is R3PLICA AI Connector?
It answers our handshake in 140 ms on average, which is faster than 84% of all working MCP servers we measure. That puts it in the quick quarter of the ecosystem. The comparison comes from our own checks across the whole registry, every 15 minutes.
How many people use R3PLICA AI Connector?
The npm package r3plica was installed 54 times in the last week. Week over week that is -20%. We show installs rather than GitHub stars on purpose: a star is a bookmark, an install is someone actually running it.