AI agents use create_model to create or update resources in SLayer — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your SLayer environment.
This tool reversibly creates data model definitions within the semantic layer. While the empty description reduces confidence, the naming pattern and sibling tool context (delete_model, edit_model) strongly suggest model creation is a Write operation—it modifies the semantic layer configuration but does not execute queries, delete irreversibly, or move money.
From the tool's definition Tool named 'create_model' with no description provided. Context from server description and sibling tools (delete_model, edit_model, describe_datasource) indicates this server manages data models and semantic layer configurations.
Documented attack patterns abuse exactly the kind of access create_model gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and SLayer, and nothing reaches the server without passing your rules. This is the rule we recommend for create_model:
{
"version": "1",
"default": "deny",
"tools": {
"create_model": {
"limits": [
{
"counter": "create_model_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}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.
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create_model. It is categorised as a Write tool in the SLayer MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the SLayer 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 SLayer. Nothing to install.
create_model 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 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.
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.
create_model is provided by the SLayer MCP server (motleyai/slayer). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from SLayer, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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20 SLayer tools catalogued and risk-classified — across an index of 43,000+ MCP servers.