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tool_call

"Use this tool to execute a specific method of another tool with the provided parameters based on get-tools tool response. You need to specify the tool name, method name, and any required parameters for that method."

Part of the VeyraX MCP server.

tool_call can trigger actions in VeyraX MCP, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

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AI agents invoke tool_call to trigger processes or run actions in VeyraX MCP. Execute operations can have side effects beyond the immediate call -- triggering builds, sending notifications, or starting workflows. Rate limits and argument validation are essential to prevent runaway execution.

tool_call can trigger processes with real-world consequences. An uncontrolled agent might start dozens of builds, send mass notifications, or kick off expensive compute jobs. PolicyLayer enforces rate limits and validates arguments to keep execution within safe bounds.

Execute tools trigger processes. Rate-limit and validate arguments to prevent unintended side effects.

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

See the full VeyraX MCP policy for all 3 tools.

Get this rule live on your own VeyraX MCP 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 tool_call 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 tool_call only ever does what you allow.

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

What does the tool_call tool do? +

"Use this tool to execute a specific method of another tool with the provided parameters based on get-tools tool response. You need to specify the tool name, method name, and any required parameters for that method.". It is categorised as a Execute tool in the VeyraX MCP MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on tool_call? +

Register the VeyraX MCP server in PolicyLayer and add a rule for tool_call: 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 VeyraX MCP. Nothing to install.

What risk level is tool_call? +

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

Can I rate-limit tool_call? +

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

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

tool_call is provided by the VeyraX MCP server (clarenous/veyrax-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every VeyraX MCP tool call.

Deterministic rules across all 3 VeyraX MCP tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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4,600+ MCP servers and 31,000+ tools scanned and risk-classified.

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