generate_estimate_number

Generate a unique estimate number

SERVERGoHighLevel MCP Server SOURCEthinkbedo/gohighlevel_mcp

Medium RISK CLASS

Category Write

Parameters 00 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/thinkbedo-gohighlevel-mcp/generate-estimate-number.md

WHAT IT DOES

What generate_estimate_number does on GoHighLevel MCP Server

AI agents use generate_estimate_number to create or update resources in GoHighLevel MCP Server, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your GoHighLevel MCP Server environment.

RISK

Why generate_estimate_number is rated Medium

This falls under Write category because it creates new data (a unique estimate number) that becomes part of the CRM system. The severity is medium because while it modifies state by introducing new records, the operation is reversible (the estimate can be deleted or the number reassigned). It does not execute arbitrary code, delete data, or move funds.

From the tool's definition The tool 'generate_estimate_number' creates a unique identifier for estimates, which is a form of data generation/creation. The description indicates it 'generates' (creates) a new estimate number, a piece of business data.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs generate_estimate_number safely

PolicyLayer is an MCP gateway: it sits between your AI agents and GoHighLevel MCP Server, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For generate_estimate_number, this is the rule to start with:

generate_estimate_number Rate-limited

generate_estimate_number stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "generate_estimate_number": {
      "limits": [
        {
          "counter": "generate_estimate_number_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect GoHighLevel MCP Server, apply this rule, and every generate_estimate_number call is checked against it from then on.

FAQ

Questions about generate_estimate_number

What does the generate_estimate_number tool do? +

Generate a unique estimate number. It is categorised as a Write tool in the GoHighLevel MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on generate_estimate_number? +

Register the GoHighLevel MCP Server MCP server in PolicyLayer and add a rule for generate_estimate_number: 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 GoHighLevel MCP Server. Nothing to install.

What risk level is generate_estimate_number? +

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

Can I rate-limit generate_estimate_number? +

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

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

generate_estimate_number is provided by the GoHighLevel MCP Server MCP server (thinkbedo/gohighlevel_mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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