pull_model

Pull/download a model from Ollama library.

SERVERMCP Trader Server SOURCEaf7007/mcp-trader

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/af7007-mcp-trader/pull-model.md

WHAT IT DOES

What pull_model does on MCP Trader Server

AI agents invoke pull_model to trigger actions in MCP Trader Server. 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 pull_model is rated High

This tool triggers an external operation (downloading a model from the Ollama library), which has side effects beyond simple data retrieval. It executes a network operation that modifies the local system state by downloading and installing a model. It's not purely destructive, financial, or a simple read — it executes an external process with system-level effects.

From the tool's definition Pull/download a model from Ollama library

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs pull_model safely

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

pull_model Rate-limited

pull_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.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "pull_model": {
      "limits": [
        {
          "counter": "pull_model_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 MCP Trader Server, apply this rule, and every pull_model call is checked against it from then on.

FAQ

Questions about pull_model

What does the pull_model tool do? +

Pull/download a model from Ollama library. It is categorised as a Execute tool in the MCP Trader Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on pull_model? +

Register the MCP Trader Server MCP server in PolicyLayer and add a rule for pull_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 MCP Trader Server. Nothing to install.

What risk level is pull_model? +

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

Can I rate-limit pull_model? +

Yes. Add a rate_limit block to the pull_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.

How do I block pull_model completely? +

Set action: deny in the PolicyLayer policy for pull_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.

What MCP server provides pull_model? +

pull_model is provided by the MCP Trader Server MCP server (af7007/mcp-trader). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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