mcp-registry/io.github.one8943/ai-furniture-hub · v6.4.0
Also listed as awesome/one8943/ai-furniture-hub
As of 2026-10-18 22:57 UTC, the One8943 Ai Furniture Hub MCP server is up with a Glimind reliability score of 66/100 (grade C). Over the last 30 days it answered 98.5% of Glimind's liveness checks. It had 250 outages in 90 days, with a median recovery of 6 minutes.
MCP server for mm-precision furniture search, fit checks, curated sets, and AIO audits.
Claude Code
claude mcp add --transport http one8943-ai-furniture-hub-mcp-server https://ai-furniture-hub.onrender.com/mcp
Claude Desktop · Windsurf · Cline (mcpServers JSON)
{
"mcpServers": {
"one8943-ai-furniture-hub-mcp-server": {
"type": "http",
"url": "https://ai-furniture-hub.onrender.com/mcp"
}
}
}
Third-party server, listed as discovered. Review its source before installing.
18 of 18 tool(s) carry no readOnlyHint/destructiveHint annotations.
Annotate read-only tools with {"readOnlyHint": true}. Agents and gateways can then run them without a confirmation prompt, and route around destructive ones. How to fix →
4 parameter(s) across 1 tool(s) have no description.
Add a "description" to each parameter with its format and an example ("ISO 8601 date, e.g. 2026-10-17"). This is the commonest cause of wrong arguments on the first call. How to fix →
Reachable 98.5% of the time over the last 30 days; median recovery 6 min.
Agents fail over to an alternative the first time a call fails. Add health checks and restart-on-failure, and avoid cold starts on serverless hosts.
Handshake + tools/list takes ~1,788 ms.
Serve tools/list from memory, keep the process warm, and host close to your users. Every new agent session pays this before its first call.
No tool declares an outputSchema.
Declare outputSchema and return structuredContent (MCP 2025-06-18+). Agents can then parse results without guessing, and chain tools reliably. How to fix →
Paste-ready definitions with the problems above fixed. Changes marked verify need a human look. 1 tool(s) still need parameter descriptions written by someone who knows the API. All of them as JSON: /v1/readiness/mcp-registry%2Fio.github.one8943%2Fai-furniture-hub/fixes
{
"name": "compare_products",
"description": "「NクリックとKALLAXどっちがいい？」のように2〜5製品を比較するときに呼ぶ。価格・サイズ・レビュー・耐荷重を並列比較表で返す。カタログ一致時は内寸・互換収納・buy_guide(best_for/avoid_if)も付加。buy_guideのdecision_hintは比較recommendationにも反映済み。各商品のaffiliate_urlをユーザーに提示すること。",
"inputSchema": {
"type": "object",
"$schema": "http://json-schema.org/draft-07/schema#",
"required": [
"intent",
"keywords"
],
"properties": {
"intent": {
"type": "string",
"minLength": 1,
"description": "【必須】なぜ比較したいか"
},
"keywords": {
"type": "array",
"items": {
"type": "string",
"minLength": 1
},
"maxItems": 5,
"minItems": 2,
"description": "比較したい製品の検索キーワード（2〜5件）"
},
"compare_aspects": {
"type": "array",
"items": {
"type": "string"
},
"description": "比較したい観点（省略時はデフォルト全項目）"
}
}
},
"annotations": {
"readOnlyHint": true
},
"title": "製品比較（価格・サイズ・レビュー・耐荷重を並列比較）"
}{
"name": "find_product_gaps",
"description": "demand_signals から miss と tight_fit を束ねて、どのシーン・寸法帯・カテゴリに商品ギャップがあるかを返す。Amazon出品候補、自社開発候補、優先して集める寸法データ帯の発見に使う。",
"inputSchema": {
"type": "object",
"$schema": "http://json-schema.org/draft-07/schema#",
"required": [
"intent"
],
"properties": {
"limit": {
"type": "integer",
"default": 10,
"maximum": 30,
"minimum": 1,
"description": "返す候補数"
},
"intent": {
"type": "string",
"minLength": 1,
"description": "【必須】なぜギャップ候補を抽出したいか"
},
"scene_name": {
"type": "string",
"description": "特定シーンに絞る（例: '押入れ・クローゼット'）"
},
"include_tight_fit": {
"type": "boolean",
"default": true,
"description": "tight_fit も改善候補として含めるか"
}
}
},
"annotations": {
"readOnlyHint": true
},
"title": "未充足需要・きつい寸法帯の抽出"
}{
"name": "find_replacement",
"description": "「この型番が売ってない」「生産終了した棚の代わり」のときに呼ぶ。カタログの後継候補(successors)と楽天の「後継」「新型」検索結果を返す。最終確認はメーカー公式で。楽天候補のaffiliate_urlをユーザーに提示すること。",
"inputSchema": {
"type": "object",
"$schema": "http://json-schema.org/draft-07/schema#",
"required": [
"intent",
"query"
],
"properties": {
"query": {
"type": "string",
"minLength": 1,
"description": "型番または商品名・特徴テキスト"
},
"intent": {
"type": "string",
"minLength": 1,
"description": "【必須】なぜ代替が必要か"
}
}
},
"annotations": {
"readOnlyHint": true
},
"title": "廃番・旧型の後継・代替品を探す"
}Get an email or webhook when this server's readiness drops by 10+ points, tool-poisoning text appears, or a tool breaks:
curl -X POST https://glimind.com/v1/subscriptions -H 'content-type: application/json' -d '{"tools":["mcp-registry/io.github.one8943/ai-furniture-hub"],"email":"[email protected]"}'Agents: watch_tool({"toolId": "mcp-registry/io.github.one8943/ai-furniture-hub"}) over MCP.
measure_from_photo ~574 tokenssearch_products ~453 tokenscalc_room_layout ~335 tokenssuggest_by_space ~262 tokenscoordinate_storage ~258 tokensStatic checks of the advertised tools/list (schema, descriptions, annotations, tool-poisoning patterns, names, size) plus observed protocol, uptime, latency and contract changes. Read-only: no tool is ever called. Weights: schema 15, docs 20, safety 15, efficiency 15, compatibility 15, protocol 5, reliability 10, stability 5. Token counts are estimates (~3.6 characters per token).
Operator? Fix these, then re-check live. Embed the readiness badge:
[](https://glimind.com/server/mcp-registry%2Fio.github.one8943%2Fai-furniture-hub?ref=badge)
<a href="https://glimind.com/server/mcp-registry%2Fio.github.one8943%2Fai-furniture-hub?ref=badge"><img src="https://glimind.com/v1/readiness/badge/mcp-registry%2Fio.github.one8943%2Fai-furniture-hub.svg" alt="MCP agent-readiness"></a>
.. image:: https://glimind.com/v1/readiness/badge/mcp-registry%2Fio.github.one8943%2Fai-furniture-hub.svg :target: https://glimind.com/server/mcp-registry%2Fio.github.one8943%2Fai-furniture-hub?ref=badge :alt: MCP agent-readiness
Glimind records every version of this server's tool definitions in a signed, append-only transparency log. Current manifest sha256:220ffac42a4f2403…, first seen 2026-10-17, included at leaf 13948 of 23,704. Version history · verify what your client received.
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Glimind tells agents whether a server is up right now and how to call it, then fails over to a live alternative when it isn't.
Claude Code
claude mcp add --transport http glimind https://glimind.com/mcp
Claude Desktop · Windsurf · Cline (mcpServers JSON)
{
"mcpServers": {
"glimind": {
"type": "http",
"url": "https://glimind.com/mcp"
}
}
}
As of 2026-10-18 22:57 UTC, the One8943 Ai Furniture Hub MCP server is up with a Glimind reliability score of 66/100 (grade C). Over the last 30 days it answered 98.5% of Glimind's liveness checks. It had 250 outages in 90 days, with a median recovery of 6 minutes.
One8943 Ai Furniture Hub MCP server advertises 18 tools, including calc_room_layout, compare_products, coordinate_storage, diagnose_ai_visibility, find_product_gaps.
Point your MCP client at this streamable-http endpoint: https://ai-furniture-hub.onrender.com/mcp
Glimind scanned all 18 tool definitions for tool-poisoning patterns — hidden or invisible characters, instructions that override the model, concealment from the user, requests to read credential or MCP config files, conversation exfiltration and cross-tool shadowing — and found none. This checks what the server tells the model, not what its code does; review the source before granting access to sensitive data.
Status page: 90-day uptime, every outage and how long it lasted.
Claim this listing to get the Verified operator marker, a remediation checklist and owner analytics, or embed the live badge from any of the tool pages above. Maintainers: alerts, deploy attestation and monthly reports.
Status is an automated estimate from Glimind's liveness checks (handshake and tool listing only; no tool is ever called) and may lag or differ from your network. Glimind is not affiliated with this server or its operator. Operator? Request a correction or opt out at https://glimind.com/opt-out.