ollama_pull · ML Lab MCP: Risk & Policy

WHAT IT DOES

What ollama_pull does on ML Lab MCP

AI agents invoke ollama_pull to trigger actions in ML Lab 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 IT NEEDS A POLICY

Why ollama_pull needs a policy

Pulling a model triggers an external network operation that downloads and installs a model into the local Ollama environment. This is not a simple read (it has side effects on local storage and system state) nor purely a write (it involves executing a remote fetch and installation process). Misuse could result in downloading large, unexpected, or malicious models consuming significant disk space and bandwidth.

From the tool's definition Pull a model from the Ollama registry

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

ollama_pull Rate-limited

ollama_pull 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": {
    "ollama_pull": {
      "limits": [
        {
          "counter": "ollama_pull_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches ML Lab MCP, so you can run agents against it safely.

FAQ

Questions about ollama_pull

What does the ollama_pull tool do? +

Pull a model from the Ollama registry. It is categorised as a Execute tool in the ML Lab 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 ollama_pull? +

Register the ML Lab MCP server in PolicyLayer and add a rule for ollama_pull: 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 ML Lab MCP. Nothing to install.

What risk level is ollama_pull? +

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

Can I rate-limit ollama_pull? +

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

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

ollama_pull is provided by the ML Lab MCP server (pushpullcommitpush/ml-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.