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execute_browserql

Execute BrowserQL GraphQL queries

How to control execute_browserql ↓

What execute_browserql does on Browserless MCP Server

AI agents invoke execute_browserql to trigger actions in Browserless MCP Server. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.

High Risk

Why execute_browserql needs a policy

This is an Execute category tool because it runs queries/code whose side effects depend on the query arguments provided. While the tool itself doesn't destructively delete data or handle financial transactions, it enables arbitrary execution of GraphQL queries against a browser automation backend, which can trigger any operation the Browserless API supports (including potentially accessing sensitive data, modifying…

From the tool's definition Tool enables execution of arbitrary BrowserQL GraphQL queries against a browser automation system. The name 'execute_browserql' and description 'Execute BrowserQL GraphQL queries' indicate the ability to run user-supplied queries that can trigger complex…

Documented attack patterns abuse exactly the kind of access execute_browserql gives an agent:

How to control execute_browserql

PolicyLayer is an MCP gateway — it sits between your AI agents and Browserless MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for execute_browserql:

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "execute_browserql": {
      "limits": [
        {
          "counter": "execute_browserql_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

execute_browserql stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.

  1. Create a free account and register Browserless MCP Server — nothing to install.
  2. Add this policy — paste it, or build it visually.
  3. Point your MCP client (Claude, Cursor, anything) at your gateway URL.
RATE-LIMIT THIS TOOL →

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Related tools and policies

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Questions about execute_browserql

What does the execute_browserql tool do? +

Execute BrowserQL GraphQL queries. It is categorised as a Execute tool in the Browserless MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on execute_browserql? +

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

What risk level is execute_browserql? +

execute_browserql is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit execute_browserql? +

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

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

execute_browserql is provided by the Browserless MCP Server MCP server (lizzard-solutions/browserless-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Browserless MCP Server tool call.

Start from Browserless MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

Free to start. No card required.

16 Browserless MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.

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