update_submodel_value
AI agents use update_submodel_value to create or update resources in Aas — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Aas environment.
This tool creates or modifies data reversibly without permanently destroying it, fitting the Write category. However, the confidence is not higher (would be 0.95) because the tool description is empty, preventing full verification of scope.
From the tool's definition Tool name 'update_submodel_value' indicates modification of existing data. Server description states it enables 'full CRUD operations' on 'Submodels' via REST API. The 'update' operation is explicitly a Write action that modifies data reversibly.
Documented attack patterns abuse exactly the kind of access update_submodel_value gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Aas, and nothing reaches the server without passing your rules. This is the rule we recommend for update_submodel_value:
{
"version": "1",
"default": "deny",
"tools": {
"update_submodel_value": {
"limits": [
{
"counter": "update_submodel_value_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}update_submodel_value 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.
Free to start. No card required.
update_submodel_value. It is categorised as a Write tool in the Aas MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Aas MCP server in PolicyLayer and add a rule for update_submodel_value: 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 Aas. Nothing to install.
update_submodel_value is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the update_submodel_value 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.
Set action: deny in the PolicyLayer policy for update_submodel_value. 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.
update_submodel_value is provided by the Aas MCP server (smartfactory-kl/aas-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Aas, 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.
25 Aas tools catalogued and risk-classified — across an index of 43,000+ MCP servers.