Medium Risk

close_search_leads

Search or list leads (companies/accounts in Close) using Close's query language. Returns a data array of leads (with id, display_name, contacts, status, custom fields) plus has_more and total_results. The query param accepts Close search syntax, e.g. name:"Acme", status_label:"Potential", email_a...

Risk signalsAccepts freeform code/query input (query)

Part of the Close Crm server.

close_search_leads can modify Close Crm data, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

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AI agents use close_search_leads to create or modify resources in Close Crm. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.

Without a policy, an AI agent could call close_search_leads repeatedly, creating or modifying resources faster than any human could review. PolicyLayer's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Close Crm.

Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "close_search_leads": {
      "limits": [
        {
          "counter": "close_search_leads_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

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These attack patterns abuse exactly the kind of access close_search_leads 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 close_search_leads only ever does what you allow.

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Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.

What does the close_search_leads tool do? +

Search or list leads (companies/accounts in Close) using Close's query language. Returns a data array of leads (with id, display_name, contacts, status, custom fields) plus has_more and total_results. The query param accepts Close search syntax, e.g. name:"Acme", status_label:"Potential", email_address:@example.com, lead_created_within:7d, or free text. Omit query to list all leads. Page with _limit (max 200) and _skip.. It is categorised as a Write tool in the Close Crm MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on close_search_leads? +

Register the Close Crm MCP server in PolicyLayer and add a rule for close_search_leads: 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 Close Crm. Nothing to install.

What risk level is close_search_leads? +

close_search_leads is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit close_search_leads? +

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

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

close_search_leads is provided by the Close Crm MCP server (https://gateway.pipeworx.io/close-crm/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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