generate_from_multiple_samples · Apitype MCP: Risk & Policy

WHAT IT DOES

What generate_from_multiple_samples does on Apitype

AI agents use generate_from_multiple_samples to create or update resources in Apitype — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Apitype environment.

WHY IT NEEDS A POLICY

Why generate_from_multiple_samples needs a policy

This tool generates and outputs type definitions or schema files based on JSON input samples. While it produces output artifacts (Write), these are transformations of provided data into schema/type definitions rather than executing code. The output is reversible (types can be regenerated or discarded) and has no side effects on external systems.

From the tool's definition Tool name 'generate_from_multiple_samples' and description indicate it 'Generate types from multiple JSON samples'. The tool creates/generates TypeScript types, Zod schemas, or similar artifacts based on provided input data.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

generate_from_multiple_samples Rate-limited

generate_from_multiple_samples stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "generate_from_multiple_samples": {
      "limits": [
        {
          "counter": "generate_from_multiple_samples_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL →

Instant setup, no code required.

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

FAQ

Questions about generate_from_multiple_samples

What does the generate_from_multiple_samples tool do? +

Generate types from multiple JSON samples to correctly detect nullable and optional fields. It is categorised as a Write tool in the Apitype MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on generate_from_multiple_samples? +

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

What risk level is generate_from_multiple_samples? +

generate_from_multiple_samples is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit generate_from_multiple_samples? +

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

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

generate_from_multiple_samples is provided by the Apitype MCP server (jayesh-bansal/apitype). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.