tf_apply

Ejecuta terraform apply.

SERVERMCP Framework Personal SOURCEinggerman/mcps

Medium RISK CLASS

Category Write

Parameters 00 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/inggerman-mcps/tf-apply.md

WHAT IT DOES

What tf_apply does on MCP Framework Personal

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

RISK

Why tf_apply is rated Medium

An AI agent can call tf_apply faster than any human can review: one bad instruction and it creates or modifies resources in MCP Framework Personal by the hundred, each call as confident as the last.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs tf_apply safely

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

tf_apply Rate-limited

tf_apply 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": {
    "tf_apply": {
      "limits": [
        {
          "counter": "tf_apply_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect MCP Framework Personal, apply this rule, and every tf_apply call is checked against it from then on.

FAQ

Questions about tf_apply

What does the tf_apply tool do? +

Ejecuta terraform apply. It is categorised as a Write tool in the MCP Framework Personal MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on tf_apply? +

Register the MCP Framework Personal MCP server in PolicyLayer and add a rule for tf_apply: 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 Framework Personal. Nothing to install.

What risk level is tf_apply? +

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

Can I rate-limit tf_apply? +

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

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

tf_apply is provided by the MCP Framework Personal MCP server (inggerman/mcps). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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