Low Risk

list_popular

List the most popular Spark assets by download count. Args: type: Filter by asset type (agent, skill, prompt, prompt_chain, mcp_connector, bundle) limit: Number of results (1-20, default 10)

Part of the Spark - AI Assets Marketplace server.

list_popular 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 list_popular to retrieve information from Spark - AI Assets Marketplace 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 list_popular 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": {
    "list_popular": {}
  }
}

See the full Spark - AI Assets Marketplace policy for all 5 tools.

Get this rule live on your own Spark - AI Assets Marketplace 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 list_popular 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 list_popular 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 list_popular tool do? +

List the most popular Spark assets by download count. Args: type: Filter by asset type (agent, skill, prompt, prompt_chain, mcp_connector, bundle) limit: Number of results (1-20, default 10). It is categorised as a Read tool in the Spark - AI Assets Marketplace MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on list_popular? +

Register the Spark - AI Assets Marketplace MCP server in PolicyLayer and add a rule for list_popular: 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 Spark - AI Assets Marketplace. Nothing to install.

What risk level is list_popular? +

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

Can I rate-limit list_popular? +

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

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

list_popular is provided by the Spark - AI Assets Marketplace MCP server (howard-eridani/spark). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Spark - AI Assets Marketplace tool call.

Deterministic rules across all 5 Spark - AI Assets Marketplace tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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