Find computation models that use a given resource in data binding. This API helps you find computation models which are bound to a given resource: - Asset model (fetch all computation models where any of this asset model's properties are bound) - Asset (fetch all computation models where any of ...
Single-target operation
Part of the AWS IoT SiteWise MCP Server MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.
AI agents call list_computation_model_data_binding_usages to retrieve information from AWS IoT SiteWise MCP Server without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.
Even though list_computation_model_data_binding_usages only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.
Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.
tools:
list_computation_model_data_binding_usages:
rules:
- action: allowSee the full AWS IoT SiteWise MCP Server policy for all 72 tools.
Agents calling read-class tools like list_computation_model_data_binding_usages have been implicated in these attack patterns. Read the full case and prevention policy for each:
Other tools in the Read risk category across the catalogue. The same policy patterns (rate-limit, allow) apply to each.
Find computation models that use a given resource in data binding. This API helps you find computation models which are bound to a given resource: - Asset model (fetch all computation models where any of this asset model's properties are bound) - Asset (fetch all computation models where any of this asset's properties are bound) - Asset model property (fetch all computation models where this property is bound) - Asset property (fetch all computation models where this property is bound) Args: data_binding_value_filter: Filter to specify which resource to search for (required) region: AWS region (default: us-east-1) max_results: Optional maximum number of results to return (1-250) next_token: Optional token for pagination to get the next set of results Returns: Dictionary containing the list of computation models that use the specified resource. Filter Examples: # Find computation models using any property from a specific asset data_binding_value_filter = { "asset": { "assetId": "12345678-1234-1234-1234-123456789012" } } # Find computation models using any property from a specific asset model data_binding_value_filter = { "assetModel": { "assetModelId": "12345678-1234-1234-1234-123456789012" } } # Find computation models using a specific asset property data_binding_value_filter = { "assetProperty": { "assetId": "12345678-1234-1234-1234-123456789012", "propertyId": "87654321-4321-4321-4321-210987654321" } } # Find computation models using a specific asset model property data_binding_value_filter = { "assetModelProperty": { "assetModelId": "12345678-1234-1234-1234-123456789012", "propertyId": "87654321-4321-4321-4321-210987654321" } } Usage Examples: # Find all computation models using properties from a specific asset result = list_computation_model_data_binding_usages( data_binding_value_filter={ "asset": {"assetId": "12345678-1234-1234-1234-123456789012"} } ) # Find computation models using a specific asset property with pagination result = list_computation_model_data_binding_usages( data_binding_value_filter={ "assetProperty": { "assetId": "12345678-1234-1234-1234-123456789012", "propertyId": "87654321-4321-4321-4321-210987654321" } }, max_results=50 ) Use Cases: - Check if an asset property is already bound to a computation model before binding it elsewhere - Find all computation models that depend on a specific asset or asset model - Audit which computation models are using properties from a particular asset - Identify dependencies before deleting or modifying assets/properties. It is categorised as a Read tool in the AWS IoT SiteWise MCP Server MCP Server, which means it retrieves data without modifying state.
Add a rule in your Intercept YAML policy under the tools section for list_computation_model_data_binding_usages. 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.
list_computation_model_data_binding_usages is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the list_computation_model_data_binding_usages 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 list_computation_model_data_binding_usages. 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.
list_computation_model_data_binding_usages 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.