create_model · Langfuse Mcp Python MCP: Risk & Policy

WHAT IT DOES

What create_model does on Langfuse Mcp Python

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

WHY IT NEEDS A POLICY

Why create_model needs a policy

This tool creates a new model configuration object with pricing parameters. This is a reversible write operation—the configuration can be updated or deleted later. It does not execute arbitrary code, delete data irreversibly, move money, or trigger external side effects beyond creating a database record.

From the tool's definition Tool name is 'create_model' and description states it will 'Create a custom model configuration with pricing.' The verb 'Create' indicates data creation, and 'custom model configuration' suggests reversible resource creation.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

create_model Rate-limited

create_model 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": {
    "create_model": {
      "limits": [
        {
          "counter": "create_model_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 Langfuse Mcp Python, so you can run agents against it safely.

FAQ

Questions about create_model

What does the create_model tool do? +

Create a custom model configuration with pricing. It is categorised as a Write tool in the Langfuse Mcp Python MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on create_model? +

Register the Langfuse Mcp Python MCP server in PolicyLayer and add a rule for create_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 Langfuse Mcp Python. Nothing to install.

What risk level is create_model? +

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

Can I rate-limit create_model? +

Yes. Add a rate_limit block to the create_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 create_model completely? +

Set action: deny in the PolicyLayer policy for create_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 create_model? +

create_model is provided by the Langfuse Mcp Python MCP server (log-logn/langfuse-mcp-python). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.