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Overview

This guide provides practical examples of how to use SensorUp MCP tools with AI assistants. These examples demonstrate common use cases and best practices.

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Basic Queries

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Listing Assets

Prompt: 
Using the SensorUp MCP tool, show me all my assets
What Happens: The AI assistant will use the Asset Tool to query your assets and present them in a readable format. Expected Response:
  • List of asset names and IDs
  • Asset status information
  • Basic metadata

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Getting Emission Events

Prompt: 
Show me emission events from the last 7 days using SensorUp MCP
What Happens: The AI assistant will use the Event Tool with appropriate date filters to retrieve recent emission events. Expected Response:
  • List of emission events
  • Event dates and times
  • Event status and details

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Advanced Queries

Prompt: 
Using SensorUp MCP, analyze emission trends for the last 30 days and identify any patterns
What Happens: The AI assistant will:
  1. Use the Analytics Tool to retrieve emission data
  2. Process the data to identify trends
  3. Present insights in a clear format
Expected Response:
  • Trend analysis
  • Pattern identification
  • Data visualization suggestions

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Asset Status Monitoring

Prompt: 
Check the status of all my assets and alert me to any that are inactive
What Happens: The AI assistant will:
  1. Query all assets using the Asset Tool
  2. Filter by status
  3. Highlight inactive assets
Expected Response:
  • Summary of asset statuses
  • List of inactive assets
  • Suggested actions

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Complex Workflows

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Event Investigation

Prompt: 
Using SensorUp MCP, find the emission event with the highest rate from last month and show me its details including associated assets
What Happens: The AI assistant will:
  1. Query emission events from last month
  2. Identify the event with the highest rate
  3. Retrieve detailed event information
  4. Query associated asset data
  5. Present a comprehensive report
Expected Response:
  • Event details
  • Emission rate information
  • Associated asset information
  • Timeline data

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Custom Reporting

Prompt: 
Create a summary report of my emission operations for the last quarter using SensorUp MCP
What Happens: The AI assistant will:
  1. Query emission events for the quarter
  2. Retrieve relevant analytics
  3. Aggregate the data
  4. Format it as a report
Expected Response:
  • Summary statistics
  • Key metrics
  • Trend analysis
  • Comparative data

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Integration Patterns

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Daily Monitoring

Use Case: Set up daily emission monitoring Prompt: 
Check my SensorUp data for any new emission events today and summarize them
Benefits:
  • Quick daily updates
  • Early issue detection
  • Consistent monitoring

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Asset Health Checks

Use Case: Regular asset status reviews Prompt: 
Review the health status of all my assets and identify any that need attention
Benefits:
  • Proactive maintenance
  • Status visibility
  • Operational insights

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Best Practices

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1. Be Specific with Time Ranges

Good: “Show me events from the last 7 days” Better: “Show me emission events from January 1-7, 2025”

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2. Request Relevant Fields

Good: “Get asset data” Better: “Get asset names, IDs, and current status”

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3. Use Follow-up Questions

Start broad, then drill down:
  1. “Show me all emission events”
  2. “Show me details for event #12345”
  3. “What assets are associated with that event?“

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4. Combine Multiple Queries

Ask for related data in one prompt: “Show me emission events from last week and the associated asset status for each event”

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Troubleshooting

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No Data Returned

Issue: Query returns empty results Solutions:
  • Verify date ranges are correct
  • Check filter parameters
  • Confirm you have data for the requested period

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Permission Errors

Issue: Tool reports insufficient permissions Solutions:
  • Verify your API key permissions
  • Check user role assignments
  • Contact your administrator

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Rate Limit Reached

Issue: Tool reports rate limit exceeded Solutions:
  • Wait before making additional requests
  • Reduce query frequency
  • Optimize query patterns