models_serve

Start Ollama server if not running.

SERVERYaver SOURCEyaver-cli

High RISK CLASS

Category Execute

Parameters 00 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/io-github-kivanccakmak-yaver/models-serve.md

WHAT IT DOES

What models_serve does on Yaver

AI agents invoke models_serve to trigger actions in Yaver. 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 models_serve is rated High

This tool executes a command to launch a server process. While starting a service is potentially reversible (via stopping it), the execution of system-level processes and server startup affects the operational state of the environment. This is an Execute action because it runs an external operation (Ollama server initialization) whose effects depend on system state.

From the tool's definition Tool name is 'models_serve' with description 'Start Ollama server if not running.' The verb 'Start' indicates the tool triggers execution of an external service (Ollama server).

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs models_serve safely

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

models_serve Rate-limited

models_serve 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": {
    "models_serve": {
      "limits": [
        {
          "counter": "models_serve_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 Yaver, apply this rule, and every models_serve call is checked against it from then on.

FAQ

Questions about models_serve

What does the models_serve tool do? +

Start Ollama server if not running. It is categorised as a Execute tool in the Yaver MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on models_serve? +

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

What risk level is models_serve? +

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

Can I rate-limit models_serve? +

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

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

models_serve is provided by the Yaver MCP server (yaver-cli). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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