Create an asset model in AWS IoT SiteWise. Args: asset_model_name: A unique, friendly name for the asset model region: AWS region (default: us-east-1) asset_model_description: A description for the asset model asset_model_properties: The property definitions of the asset model ...
High parameter count (11 properties)
Part of the AWS IoT SiteWise MCP Server MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.
AI agents use create_asset_model to create or modify resources in AWS IoT SiteWise MCP Server. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.
Without a policy, an AI agent could call create_asset_model repeatedly, creating or modifying resources faster than any human could review. Intercept's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach AWS IoT SiteWise MCP Server.
Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.
tools:
create_asset_model:
rules:
- action: allow
rate_limit:
max: 30
window: 60See the full AWS IoT SiteWise MCP Server policy for all 72 tools.
Agents calling write-class tools like create_asset_model have been implicated in these attack patterns. Read the full case and prevention policy for each:
Other tools in the Write risk category across the catalogue. The same policy patterns (rate-limit, validate) apply to each.
Create an asset model in AWS IoT SiteWise. Args: asset_model_name: A unique, friendly name for the asset model region: AWS region (default: us-east-1) asset_model_description: A description for the asset model asset_model_properties: The property definitions of the asset model asset_model_hierarchies: The hierarchy definitions of the asset model asset_model_composite_models: The composite models that are part of this asset model client_token: A unique case-sensitive identifier for the request tags: A list of key-value pairs that contain metadata for the asset model asset_model_id: The ID to assign to the asset model asset_model_external_id: An external ID to assign to the asset model asset_model_type: The type of asset model ( ASSET_MODEL, COMPONENT_MODEL) Returns: Dictionary containing asset model creation response. It is categorised as a Write tool in the AWS IoT SiteWise MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Add a rule in your Intercept YAML policy under the tools section for create_asset_model. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the AWS IoT SiteWise MCP Server MCP server.
create_asset_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_asset_model rule in your Intercept 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 Intercept policy for create_asset_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_asset_model is provided by the AWS IoT SiteWise MCP Server MCP server (awslabs.aws-iot-sitewise-mcp-server). Intercept sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic policy on every MCP tool call. Per-identity grants. Full audit log.