Low Risk

search_products

Search products in the connected store by keyword. Use this when a shopper's query suggests specific terms the agent can match against product titles or tags — e.g. "HEPA air purifier" or "leather wristwatch". Matches Shopify's native storefront search behavior, so results align with what custome...

Risk signalsAccepts freeform code/query input (query)

Part of the Agentic Shelf server.

search_products 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 search_products to retrieve information from Agentic Shelf 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 search_products 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": {
    "search_products": {}
  }
}

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Get this rule live on your own Agentic Shelf server in minutes. PolicyLayer enforces it on every call, before it runs.

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

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Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so search_products 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 search_products tool do? +

Search products in the connected store by keyword. Use this when a shopper's query suggests specific terms the agent can match against product titles or tags — e.g. "HEPA air purifier" or "leather wristwatch". Matches Shopify's native storefront search behavior, so results align with what customers would find on the site. Args: query: Keyword or phrase to match. limit: Max products to return (1-50, default 10). Returns: Same shape as list_products. Empty products list when no matches.. It is categorised as a Read tool in the Agentic Shelf MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on search_products? +

Register the Agentic Shelf MCP server in PolicyLayer and add a rule for search_products: 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 Agentic Shelf. Nothing to install.

What risk level is search_products? +

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

Can I rate-limit search_products? +

Yes. Add a rate_limit block to the search_products 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 search_products completely? +

Set action: deny in the PolicyLayer policy for search_products. 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 search_products? +

search_products is provided by the Agentic Shelf MCP server (https://api.agenticshelf.ai/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Agentic Shelf tool call.

Deterministic rules across all 5 Agentic Shelf tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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4,600+ MCP servers and 31,000+ tools scanned and risk-classified.

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