Low Risk

get_store_template_install_options

Returns the displays the authenticated user can send a given store template to, plus the data slots the template needs. Call this before send_store_template_to_display so you can show the user which Türschild they can target and know which per-slot JSON the template consumes. Requires authenticat...

Risk signalsHandles credentials or secrets (access_token)

Part of the agentView server.

get_store_template_install_options 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 get_store_template_install_options to retrieve information from agentView 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 get_store_template_install_options 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": {
    "get_store_template_install_options": {}
  }
}

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These attack patterns abuse exactly the kind of access get_store_template_install_options 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 get_store_template_install_options 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 get_store_template_install_options tool do? +

Returns the displays the authenticated user can send a given store template to, plus the data slots the template needs. Call this before send_store_template_to_display so you can show the user which Türschild they can target and know which per-slot JSON the template consumes. Requires authentication with at least content_only scope. API-key callers scoped to a display whitelist only see their scoped displays. When no displays come back, tell the user they first need to create/claim a display (create_display / pair_by_code) before installing store content.. It is categorised as a Read tool in the agentView MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on get_store_template_install_options? +

Register the agentView MCP server in PolicyLayer and add a rule for get_store_template_install_options: 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 agentView. Nothing to install.

What risk level is get_store_template_install_options? +

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

Can I rate-limit get_store_template_install_options? +

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

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

get_store_template_install_options is provided by the agentView MCP server (https://agentview.de/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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