Low Risk

train

Train a gradient boosting model and return portable artifacts (joblib and/or ONNX)

Part of the WarpGBM server.

train is read-only, but an agent in a loop can still rack up calls and cost. PolicyLayer caps every call before it runs. Live in minutes.

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Free to start. No card required.

AI agents call train to retrieve information from WarpGBM without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.

Even though train only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.

Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "train": {}
  }
}

See the full WarpGBM policy for all 6 tools.

Get this rule live on your own WarpGBM server in minutes. PolicyLayer enforces it on every call, before it runs.

ENFORCE ON MY WARPGBM →

These attack patterns abuse exactly the kind of access train gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so train only ever does what you allow.

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Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.

What does the train tool do? +

Train a gradient boosting model and return portable artifacts (joblib and/or ONNX). It is categorised as a Read tool in the WarpGBM MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on train? +

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

What risk level is train? +

train is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit train? +

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

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

train is provided by the WarpGBM MCP server (jefferythewind/warpgbm-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every WarpGBM tool call.

Deterministic rules across all 6 WarpGBM tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

Free to start. No card required.

4,600+ MCP servers and 31,000+ tools scanned and risk-classified.

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