Create a buffered ingestion job to ingest data from Amazon S3 to AWS IoT SiteWise. This is a convenience function that calls create_bulk_import_job with adaptive_ingestion=True to enable buffered ingestion mode for real-time processing of recent data (within 30 days). Args: job_name: Unique...
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_buffered_ingestion_job 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_buffered_ingestion_job 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_buffered_ingestion_job:
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_buffered_ingestion_job 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 a buffered ingestion job to ingest data from Amazon S3 to AWS IoT SiteWise. This is a convenience function that calls create_bulk_import_job with adaptive_ingestion=True to enable buffered ingestion mode for real-time processing of recent data (within 30 days). Args: job_name: Unique name for the job (1-256 characters, no control characters) job_role_arn: IAM role ARN that allows IoT SiteWise to read S3 data (optional - ask the user if you can use create_bulk_import_iam_role helper function to create one.) files: List of S3 file objects with bucket, key, and optional versionId error_report_location: S3 location for error reports (bucket and prefix) job_configuration: Configuration including file format (CSV or Parquet) delete_files_after_import: Delete S3 files after ingestion (default: False) region: AWS region (default: us-east-1) Returns: Dictionary containing job creation response with jobId, jobName, and jobStatus Example: files = [{"bucket": "my-data-bucket", "key": "data/timeseries.csv"}] error_location = {"bucket": "my-error-bucket", "prefix": "errors/"} job_config = { "fileFormat": { "csv": { "columnNames": ["ALIAS", "TIMESTAMP_SECONDS", "VALUE", "QUALITY"] } } } result = create_buffered_ingestion_job( job_name="my-buffered-ingestion-job", job_role_arn="arn:aws:iam::123456789012:role/IoTSiteWiseRole", files=files, error_report_location=error_location, job_configuration=job_config ). 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_buffered_ingestion_job. 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_buffered_ingestion_job 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_buffered_ingestion_job 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_buffered_ingestion_job. 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_buffered_ingestion_job 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.