fit_predict

THE RISK

High Risk

Why fit_predict needs a policy

This tool executes a computational workflow: it trains (fits) a model and then generates predictions. This is an active execution of code/algorithms whose effects depend on the arguments supplied (estimator type, data, parameters). It is not a simple read/query, and it may consume significant resources or produce downstream effects if results are used in pipelines. Most severe applicable category is Execute.

From the tool's definition "Fit an estimator and generate predictions" — runs a machine learning workflow (fitting + inference) on provided data

Documented attack patterns abuse exactly the kind of access fit_predict gives an agent:

POLICY

How to control fit_predict

PolicyLayer is an MCP gateway — it sits between your AI agents and Sktime, and nothing reaches the server without passing your rules. This is the rule we recommend for fit_predict:

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "fit_predict": {
      "limits": [
        {
          "counter": "fit_predict_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

fit_predict 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.

Create a free account and register Sktime — nothing to install.
Add this policy — paste it, or build it visually.
Point your MCP client (Claude, Cursor, anything) at your gateway URL.

RATE-LIMIT THIS TOOL →

Free to start. No card required.

EXPLORE

Related tools and policies

More Sktime tools

Destructive cancel_job Cancel a running or pending background job. Destructive release_data_handle Release a data handle and free memory Execute evaluate_estimator Evaluate an estimator using cross-validation on a dataset Execute fit_predict_async Fit an estimator and generate predictions in the background. Execute fit_predict_classification Fit a time series classifier on training data and predict class labels on test data. Use w Execute fit_predict_regression Fit a time series regressor on training data and predict continuous target values on test Execute instantiate_estimator Create an estimator instance with given parameters Write format_time_series Automatically format time series data (frequency, duplicates, missing values)

All 24 Sktime tools →

Execute tools on other servers

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Go deeper

High-risk tools in Sktime → Every high-risk tool this server exposes, in one view.
All high-risk MCP tools → Every high-risk tool across the catalogue, and the policy pattern that contains them.
The MCP Attack Database → Documented attack patterns against MCP deployments — and the policies that stop them.
Agent sandbox → Bounding what an agent can execute and where the boundary should sit.
Least privilege for MCP → Granting agents the minimum tool surface the task needs.
Rate Limiting MCP Tool Calls: A Practical Guide →
MCP Security: Why Prompt Guardrails Aren't Enough →

FAQ

Questions about fit_predict

What does the fit_predict tool do? +

Fit an estimator and generate predictions. It is categorised as a Execute tool in the Sktime MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on fit_predict? +

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

What risk level is fit_predict? +

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

Can I rate-limit fit_predict? +

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

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

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

Enforce policy on every Sktime tool call.

Start from Sktime, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

CHECK YOUR STACK →