Microsoft Power Automate Documentation

Business approvals templates are part of the Approvals Kit and provide no-code templates built on Microsoft Power Platform components. They are designed to accelerate the creation of sophisticated approval workflows that include features like conditional branching, delegation, and administrative overrides.

Key capabilities provided by these templates include:

• Multi-stage approvals: Configure workflows with multiple steps.
• Delegation: Allow others to approve on behalf of an approver.
• Progress Tracking: View approval history and current status.
• Out of Office Management: Manage approver availability.
• Version Control: Support for different versions of approval processes and the ability to publish versioned workflows.
• Calendar Awareness: Handle work days and public holidays within the process.

The automation center is a centralized hub for monitoring and managing automation activity across Power Automate. It provides a holistic view of automation data, including execution logs, performance metrics, recommendations, and an integrated copilot. It is designed for various personas, including makers, operators, Center of Excellence (CoE) members, and business analysts.

Key capabilities include:

• Monitoring: Tracking execution, resources, and errors.
• Troubleshooting: Analyzing run history and process hierarchies.
• Value Assessment: Measuring business impact and capacity utilization.

The Process Mining Model Context Protocol (MCP) server is a specialized implementation of the MCP standard that exposes Process Mining analytics to AI agents and conversational applications. It allows for natural language interactions with process data through MCP-compatible clients like Microsoft Copilot Studio.

Key capabilities:

• Process discovery: List and explore available processes and their metadata.
• Analytics and metrics: Retrieve bottleneck analysis, variants, cases, edges, and aggregated metrics.
• Correlation analysis: Identify attribute influences on process performance.
• Advanced filtering: Apply complex filters across attributes, timeframes, metrics, subprocesses, and sequences.
• Long-running operations: Support for complex queries with progress notifications.

The flow designer is the central environment in Power Automate desktop used to design, debug, and manage desktop flows. It provides access to all flow components, including images, UI elements, and variables.

Key components of the designer include:

• Actions pane: Contains the tools and actions used to build the flow.
• Variables pane: Used to manage and view data stored in variables.
• Workspace: Displays the flow status and the data it contains.
• Subflows: Managed via tabs to organize large or complex flows.
• Debugging tools: Includes breakpoints and the ability to run a flow step-by-step.
• Error handling: Displays error information and highlights erroneous actions immediately.

The Power Automate console is the central interface for Power Automate for desktop. It consists of four main tabs:

• Home screen: The landing page.
• Your desktop flows: A list of flows owned by you.
• Shared desktop flows: Flows shared with you by others.
• Built-in examples: Pre-made flows to help you get started.

At the top of the window, you can:

• View the current user.
• Use the command bar for actions.
• Switch environments via a dropdown list.
• Access Settings and Help.
• Use the search bar to find flows.

Note: If options are disabled, you may lack sufficient permissions in the current environment. Contact your admin to adjust security roles.

Cloud flows are stored in Dataverse. You can manage them programmatically using either the Dataverse SDK for .NET or the Dataverse Web API.

Note: This method currently only supports managing flows found under the Solutions tab in Power Automate. Flows under My Flows are not supported via code.

The Process Mining MCP server provides several tools for analyzing performance, bottlenecks, and variants:

• get_process_overall_metrics: Returns aggregated process-level metrics (e.g., total cases, average duration, throughput, SLA compliance).
• get_bottleneck_analysis: Returns activities sorted by duration (descending) to identify bottlenecks. It automatically analyzes the Activity attribute.
• get_variants_with_metrics: Retrieves process variants (unique activity sequences) and their associated metrics like frequency and duration.
• get_edges_with_metrics: Retrieves transitions (edges) between activities, including frequency and duration.
• get_cases_with_metrics: Retrieves individual cases with their specific metrics and attributes for detailed investigation.

Work queue processing involves managing a list of work items (containing metadata like name, priority, expiration date, status, and value) to ensure they are completed in a specific order. You can process these queues using four primary methods:

1. Desktop flow-based processing: Using Power Automate desktop (PAD) to handle items.
2. Cloud flow and connector-based processing: Using standard cloud flow connectors.
3. Cloud flow-based processing with desktop flow support: Orchestrating desktop flows via cloud flows.
4. Dataverse pro-developer features: For advanced integration, you can interact with the work queue data directly via:
   • Dataverse Web API
   • Dataverse SDK for .NET