Low Risk

suggest_by_space

「洗面所の幅45cm×奥行30cmの隙間に何か置きたい」のようにスペース起点で探すときに呼ぶ。寸法(mm)を指定すると、そこに収まる製品をカテゴリ横断で返す。回転フィット対応(幅と奥行を入れ替えても判定)。棚+ボックスの両方が見つかればコーディネーションプランも自動生成。大型品にはcarry_in(搬入経路チェック)が付く。risk=warning/criticalならユーザーに搬入注意を伝えること。各商品のaffiliate_urlをユーザーに提示すること。

Part of the AI Furniture & Home Product Hub server.

suggest_by_space is read-only, but an agent in a loop can still rack up calls and cost. PolicyLayer caps every call before it runs. Live in minutes.

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AI agents call suggest_by_space to retrieve information from AI Furniture & Home Product Hub without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.

Even though suggest_by_space only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.

Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "suggest_by_space": {}
  }
}

See the full AI Furniture & Home Product Hub policy for all 18 tools.

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These attack patterns abuse exactly the kind of access suggest_by_space gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so suggest_by_space only ever does what you allow.

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Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.

What does the suggest_by_space tool do? +

「洗面所の幅45cm×奥行30cmの隙間に何か置きたい」のようにスペース起点で探すときに呼ぶ。寸法(mm)を指定すると、そこに収まる製品をカテゴリ横断で返す。回転フィット対応(幅と奥行を入れ替えても判定)。棚+ボックスの両方が見つかればコーディネーションプランも自動生成。大型品にはcarry_in(搬入経路チェック)が付く。risk=warning/criticalならユーザーに搬入注意を伝えること。各商品のaffiliate_urlをユーザーに提示すること。. It is categorised as a Read tool in the AI Furniture & Home Product Hub MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on suggest_by_space? +

Register the AI Furniture & Home Product Hub MCP server in PolicyLayer and add a rule for suggest_by_space: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches AI Furniture & Home Product Hub. Nothing to install.

What risk level is suggest_by_space? +

suggest_by_space is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit suggest_by_space? +

Yes. Add a rate_limit block to the suggest_by_space rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.

How do I block suggest_by_space completely? +

Set action: deny in the PolicyLayer policy for suggest_by_space. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.

What MCP server provides suggest_by_space? +

suggest_by_space is provided by the AI Furniture & Home Product Hub MCP server (https://ai-furniture-hub.onrender.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every AI Furniture & Home Product Hub tool call.

Deterministic rules across all 18 AI Furniture & Home Product Hub tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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