stop_model
Stop serving a model on this node.
This record as markdown: /tools/network-tenzro-tenzro/stop-model.md
What stop_model does on Tenzro Ledger MCP
AI agents invoke stop_model to trigger actions in Tenzro Ledger MCP. 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 stop_model is rated High
The tool executes a command to stop a model server process. While not immediately destructive (the model data persists), it disrupts service availability and represents a state-changing operation on external infrastructure. This fits Execute rather than Write because it triggers/halts an external process rather than creating/modifying data.
From the tool's definition 'Stop serving a model on this node' - this is an operational action that halts a running service/process. It triggers an external operation (stopping a model server) whose effects depend on which model is being stopped.
Attacks that exploit this kind of access
The rule that runs stop_model safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Tenzro Ledger MCP, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For stop_model, this is the rule to start with:
stop_model 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 Tenzro Ledger MCP, apply this rule, and every stop_model call is checked against it from then on.
Questions about stop_model
Stop serving a model on this node. It is categorised as a Execute tool in the Tenzro Ledger MCP MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Tenzro Ledger MCP server in PolicyLayer and add a rule for stop_model: 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 Tenzro Ledger MCP. Nothing to install.
stop_model 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 stop_model 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 stop_model. 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.
stop_model is provided by the Tenzro Ledger MCP server (https://canton-mcp.tenzro.network/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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