call_tool

Execute a tool in a group. Typical flow: list_tools → get_tool_schema → call_tool. toolName must come from list_tools results. arguments must match the tool

SERVERA2wave SOURCELilithGames/a2wave

High RISK CLASS

Category Execute

Parameters 00 required

Recommended Rate-limitedsee the rule below

Registry record Grade D, identity unverified Pull the record →

This record as markdown: /tools/a2wave/call-tool.md

WHAT IT DOES

What call_tool does on A2wave

AI agents invoke call_tool to trigger actions in A2wave. 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.

RISK

Why call_tool is rated High

Executes arbitrary tools with user-supplied arguments; effects depend on which tool and arguments are chosen.

From the tool's definition Execute a tool in a group with arguments matching tool schema.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs call_tool safely

PolicyLayer is an MCP gateway: it sits between your AI agents and A2wave, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For call_tool, this is the rule to start with:

call_tool Rate-limited

call_tool 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.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "call_tool": {
      "limits": [
        {
          "counter": "call_tool_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect A2wave, apply this rule, and every call_tool call is checked against it from then on.

FAQ

Questions about call_tool

What does the call_tool tool do? +

Execute a tool in a group. Typical flow: list_tools → get_tool_schema → call_tool. toolName must come from list_tools results. arguments must match the tool. It is categorised as a Execute tool in the A2wave MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on call_tool? +

Register the A2wave MCP server in PolicyLayer and add a rule for call_tool: 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 A2wave. Nothing to install.

What risk level is call_tool? +

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

Can I rate-limit call_tool? +

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

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

call_tool is provided by the A2wave MCP server (LilithGames/a2wave). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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