Low Risk

search_resources

Unified search across x402 services, MCP servers and A2A agents. Args: intent: Natural-language query. protocol: Optional filter: "x402", "mcp" or "a2a". top_k: Max resources to return (1-50).

Part of the agent-tools (x402 + MCP + A2A directory) server.

search_resources 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_resources to retrieve information from agent-tools (x402 + MCP + A2A directory) 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_resources 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_resources": {}
  }
}

See the full agent-tools (x402 + MCP + A2A directory) policy for all 10 tools.

Get this rule live on your own agent-tools (x402 + MCP + A2A directory) 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_resources 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 search_resources 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_resources tool do? +

Unified search across x402 services, MCP servers and A2A agents. Args: intent: Natural-language query. protocol: Optional filter: "x402", "mcp" or "a2a". top_k: Max resources to return (1-50).. It is categorised as a Read tool in the agent-tools (x402 + MCP + A2A directory) MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on search_resources? +

Register the agent-tools (x402 + MCP + A2A directory) MCP server in PolicyLayer and add a rule for search_resources: 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 agent-tools (x402 + MCP + A2A directory). Nothing to install.

What risk level is search_resources? +

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

Can I rate-limit search_resources? +

Yes. Add a rate_limit block to the search_resources 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_resources completely? +

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

search_resources is provided by the agent-tools (x402 + MCP + A2A directory) MCP server (pypi:agent-tools-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every agent-tools (x402 + MCP + A2A directory) tool call.

Deterministic rules across all 10 agent-tools (x402 + MCP + A2A directory) tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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