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Cloud InfrastructureAuto-generatedScore: 46

AWS IoT SiteWise MCP Server

The AWS IoT SiteWise API, provided by Amazon Web Services, serves as the programmatic interface to the IoT SiteWise managed service, designed to ingest, model, store, and query industrial equipment data at scale.

Quick Start Summary

The AWS IoT SiteWise MCP server is a Model Context Protocol bridge that connects AI assistants — including Claude Desktop, Cursor, Windsurf, and VS Code Copilot — to the AWS IoT SiteWise API through natural language. It exposes 10 API endpoints as callable tools, such as AssociateAssets, AssociateTimeSeriesToAssetProperty, BatchAssociateProjectAssets, and more. No authentication is required — setup takes approximately 30 seconds. The server uses STDIO transport and can be installed by running npx -y @mcp/amazonaws-com-iotsitewise. This integration is sourced from the auto AWS IoT SiteWise OpenAPI specification (v2019-12-02) and has a quality score of 46/99 (fair documentation coverage).

10Endpointstools mapped
NoneAuthopen access
46/99Qualityfair
~30 secSetupno auth

Server Details

Category
Cloud Infrastructure
Authentication
None
Endpoints
10 operations
Transport
STDIO
Spec Version
v2019-12-02
Install Command
npx -y @mcp/amazonaws-com-iotsitewise

Environment Variables

AWS_IOT_SITEWISE_API_KEY

Example: your_aws_iot_sitewise_api_key

Top Endpoints

POST
/assets/{assetId}/associate

AssociateAssets

POST
/timeseries/associate/#alias&assetId&propertyId

AssociateTimeSeriesToAssetProperty

POST
/projects/{projectId}/assets/associate

BatchAssociateProjectAssets

POST
/projects/{projectId}/assets/disassociate

BatchDisassociateProjectAssets

POST
/properties/batch/aggregates

BatchGetAssetPropertyAggregates

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📖 Detailed MCP Integration Guide

A technical breakdown of capabilities, agent workflows, and security/configuration best practices.

Capabilities & Use Cases
The AWS IoT SiteWise API, provided by Amazon Web Services, serves as the programmatic interface to the IoT SiteWise managed service, designed to ingest, model, store, and query industrial equipment data at scale. Its core capabilities revolve around defining a virtual representation of a physical industrial facility—an "asset hierarchy"—through models, assets, and properties. The API enables the creation and management of these models and assets, and critically, the ingestion of time-series data from connected industrial sensors and gateways. It provides endpoints for associating assets with projects or other assets for organizational purposes, and most importantly, for writing and retrieving time-series data. For instance, endpoints like POST /timeseries/associate and POST /properties/batch/aggregates allow for the bulk ingestion of sensor readings and the retrieval of calculated aggregates (like min, max, average), latest values, or historical data streams. Use cases span predictive maintenance, real-time monitoring of industrial operations, asset performance management, and operational analytics, allowing enterprises to transform raw IIoT data into actionable insights within the AWS Cloud ecosystem.
🤖AI Agent Value
Exposing the AWS IoT SiteWise API via a Model Context Protocol (MCP) server delivers significant value by transforming static API documentation into an actionable, dynamic toolset for AI coding assistants. An AI agent like Claude, integrated via MCP, gains the ability to interact directly with a developer's IoT SiteWise environment. This moves beyond simple code generation to enable real-time context awareness. For example, the AI can query the actual data model of a factory floor defined in SiteWise, understand the properties of a specific compressor asset, and then generate contextually perfect code to calculate a new efficiency metric using the correct property IDs. It can automate the setup of new data ingestion pipelines by programmatically creating asset models or verifying that the necessary assets exist before writing integration code. This deep integration reduces manual lookup errors, accelerates prototyping, and allows the AI to serve as a collaborative partner that understands the live industrial data landscape the developer is working within.
💬Example Workflows
Practical workflow examples demonstrate this powerful synergy. A developer could instruct an AI agent: "Query the latest temperature and pressure readings for all assets in the 'HydraulicPress' project and generate a Python script to alert if pressure exceeds 2000 PSI while temperature is above 80°C." The AI, using MCP tools, would first use the POST /projects/{projectId}/assets/associate (GET) endpoint to list relevant assets, then use POST /properties/batch/latest to fetch the current data, and finally generate precise, data-aware application code. Another dynamic task could be: "Audit the access policies attached to the 'ProductionLine' asset and update any that use overly permissive roles to the 'SiteWiseViewer' role for read-only compliance." Here, the AI could use GET /access-policies to list policies, analyze their IAM principals, and use the POST /access-policies endpoint to create new, compliant policy attachments. It could also automate bulk data backfills by writing a script that uses the POST /properties/batch/history endpoint after verifying the target assets exist.
🛡️Security & Auth
While the API description notes "None" for authentication, it is critical to understand that all actual AWS IoT SiteWise API calls require proper AWS IAM authentication using Access Keys or temporary credentials. In a real-world MCP server implementation, securing the connection is paramount. Developers must configure the MCP server with an IAM role that adheres to the principle of least privilege. For instance, a role used by an AI assistant for read-only analysis should only have permissions like iotsitewise:GetAssetPropertyValue and iotsitewise:ListAssets, avoiding destructive permissions like iotsitewise:CreateAsset or iotsitewise:DeleteAsset. The MCP server itself must be configured to securely manage and rotate AWS credentials, and network policies should ensure the AI assistant only has access to the specific IoT SiteWise API actions and resources required for its intended tasks, preventing unauthorized data exfiltration or modification.

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