Update a computation model in AWS IoT SiteWise. Updates the configuration, data binding, name, or description of an existing computation model. The computation model must be in ACTIVE state to be updated. Args: computation_model_id: The ID of the computation model to update (required, must ...
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 update_computation_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 update_computation_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:
update_computation_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 update_computation_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.
Update a computation model in AWS IoT SiteWise. Updates the configuration, data binding, name, or description of an existing computation model. The computation model must be in ACTIVE state to be updated. Args: computation_model_id: The ID of the computation model to update (required, must be in UUID format) computation_model_name: The new name of the computation model (required) computation_model_configuration: The new computation model configuration (required) computation_model_data_binding: The new variable bindings for the model (required) region: AWS region (default: us-east-1) computation_model_description: Optional new description of the computation model client_token: Optional unique identifier for idempotent requests Returns: Dictionary containing the computation model update response. Note: - The computation model must be in ACTIVE state - Returns HTTP 202 with UPDATING status on success - All configuration and data binding parameters are required even if unchanged. 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 update_computation_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.
update_computation_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 update_computation_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 update_computation_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.
update_computation_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.