call_tool
Run ANY Hermoso tool by name — including the paid-campaign, analytics and channel-admin tools that are not in this session\
This record as markdown: /tools/hermoso/call-tool.md
What call_tool does on Hermoso
AI agents invoke call_tool to trigger actions in Hermoso. 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.
Why call_tool is rated High
call_tool triggers real processes with real consequences. An agent gone sideways doesn't fire it once. It starts dozens of builds, sends mass notifications, or burns through compute before anyone looks up.
Risk signalsAdmin/system-level operation
Attacks that exploit this kind of access
The rule that runs call_tool safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Hermoso, 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 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.
The button opens the PolicyLayer dashboard: create your workspace, connect Hermoso, apply this rule, and every call_tool call is checked against it from then on.
Questions about call_tool
Run ANY Hermoso tool by name — including the paid-campaign, analytics and channel-admin tools that are not in this session\. It is categorised as a Execute tool in the Hermoso MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Hermoso 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 Hermoso. Nothing to install.
call_tool is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
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.
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.
call_tool is provided by the Hermoso MCP server (https://app.hermoso.ai/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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