tf_workspaces · RedisNexus MCP: Risk & Policy

WHAT IT DOES

What tf_workspaces does on RedisNexus

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

WHY IT NEEDS A POLICY

Why tf_workspaces needs a policy

Creating Terraform workspaces creates new isolated state environments, and selecting workspaces changes the operational context for subsequent infrastructure operations. While not immediately destructive, this is a reversible write operation with significant blast radius—an AI agent could inadvertently create multiple workspaces or select the wrong workspace, leading to infrastructure modifications in unintended…

From the tool's definition The tool description indicates it can 'create' and 'select' Terraform workspaces, which modifies infrastructure state and execution context.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

tf_workspaces Rate-limited

tf_workspaces 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_workspaces": {
      "limits": [
        {
          "counter": "tf_workspaces_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 RedisNexus, so you can run agents against it safely.

FAQ

Questions about tf_workspaces

What does the tf_workspaces tool do? +

Manage Terraform workspaces: list, create, select. It is categorised as a Write tool in the RedisNexus 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_workspaces? +

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

What risk level is tf_workspaces? +

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

Can I rate-limit tf_workspaces? +

Yes. Add a rate_limit block to the tf_workspaces 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_workspaces completely? +

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

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