Medium Risk

archimate_save_model

Save the current model to disk

How to control archimate_save_model ↓

What archimate_save_model does on ArchiMate MCP Server

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

Medium Risk

Why archimate_save_model needs a policy

This tool saves/persists architecture model data to disk. While saving is reversible (the file can be overwritten or deleted separately), it modifies the filesystem state and commits in-memory model changes to persistent storage. This is a classic Write operation—it creates or modifies data reversibly.

From the tool's definition Tool name 'archimate_save_model' and description 'Save the current model to disk' indicate a persistence operation that writes model data to storage.

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

How to control archimate_save_model

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

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "archimate_save_model": {
      "limits": [
        {
          "counter": "archimate_save_model_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

archimate_save_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.

  1. Create a free account and register ArchiMate MCP Server — nothing to install.
  2. Add this policy — paste it, or build it visually.
  3. Point your MCP client (Claude, Cursor, anything) at your gateway URL.
LIMIT THIS TOOL →

Free to start. No card required.

Related tools and policies

Go deeper

Questions about archimate_save_model

What does the archimate_save_model tool do? +

Save the current model to disk. It is categorised as a Write tool in the ArchiMate MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on archimate_save_model? +

Register the ArchiMate MCP Server MCP server in PolicyLayer and add a rule for archimate_save_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 ArchiMate MCP Server. Nothing to install.

What risk level is archimate_save_model? +

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

Can I rate-limit archimate_save_model? +

Yes. Add a rate_limit block to the archimate_save_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 archimate_save_model completely? +

Set action: deny in the PolicyLayer policy for archimate_save_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 archimate_save_model? +

archimate_save_model is provided by the ArchiMate MCP Server MCP server (thijs-hakkenberg/archimate-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every ArchiMate MCP Server tool call.

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

Free to start. No card required.

33 ArchiMate MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.

// GET IN TOUCH

Have a question or want to learn more? Send us a message.

Message sent.

We'll get back to you soon.