# Route Planner From Address Photos > Automates multi-stop route planning from photos of addresses. Collects the user's starting address, time needed at each stop, and departure time. Processes uploaded images through OCR to extract addresses, compiles them into a CSV, optimizes the route order, calculates arrival and departure times for each location, and delivers the final plan with a map image, detailed schedule, and Google Maps link. Content type: workflow Source URL: https://www.agentpmt.com/agent-workflow-skills/address-image-route-planner Markdown URL: https://www.agentpmt.com/api/agent/workflows/address-image-route-planner?format=agent-md Updated: 2026-03-21T04:23:25.717Z Author: firef1ie --- Estimated time saved: 30 minutes. ## Tools - File Management - Document OCR Agent - Web Data Convertor - Multi-Location Route Optimizer W Map - Date and Time Calculator ## Workflow Outline 1. Prompt: Make sure the user has entered the following information: 1. Your starting address 2. How long you need at each stop (in minutes) 3. What time you are leaving 4. Upload images containing the addresses you need to visit. 2. Upload Each Image: Repeat this section for each image. For each image the user provided, upload it to File Management. Collect the returned file_id values for use in the OCR step. 3. Batch File IDs for OCR: Goal: Group all uploaded File Management file_id values into batches of up to 10 for OCR processing | Inputs: List of file_id values returned from the upload step for all images | Outputs: An array of batches, where eac... 4. Upload Image to File Management: Upload the current image with File Management using action 'upload_standard'. Set expiration to 7 days if supported. Save the returned file_id for the OCR batching step. 5. Process Each OCR Batch: Repeat this section for each batch. For each batch of up to 10 File Management file_id values, send them all to the Document OCR Agent in a single call to extract addresses fr... 6. Compile Extracted Addresses: Goal: Parse all OCR results from every batch and compile a clean, structured list of addresses | Inputs: Raw OCR output from each batch containing extracted addresses and entities | Outputs: A JSON array of objects, eac... 7. OCR Batch of Images: Send all file_id values in this batch (up to 10) to the OCR tool in a single call. The tool supports up to 10 pages per request. Extract all addresses found across all images in t... 8. Create Address CSV: Convert the structured address JSON array into CSV format. The CSV should have columns: address, city, state, zip, stop_duration_minutes. This CSV serves as the organized record o... 9. Optimize Route Order: Use the starting address as the origin and all other addresses as waypoints. Optimize the route to minimize total travel time. Request a map image to be generated and a Google Map... 10. Prepare Time Calculations: Goal: Calculate the complete schedule of arrival and departure times for each stop using the optimized route order | Inputs: Optimized route with travel durations between each stop, user's departure time, and stop durat... 11. Calculate Arrival and Leave Times: Use date/time addition to calculate precise arrival and departure times for each stop. Start from the user's departure time and add travel durations and stop durations sequentiall... 12. Format Final Route Plan: Goal: Compile the final route plan into a clear, actionable summary for the user | Inputs: Optimized route order, arrival/departure times for each stop, signed URL of the route map image, Google Maps route link | Output... 13. Send Route Plan to User: Send a other request to a human. Your optimized route plan is ready. The notification includes your complete route with stop order, arrival and departure times for each loc... ## Frequently Asked Questions ### How do I connect this workflow to my local agent like OpenClaw or Claude Code? You can install the local MCP server by opening a terminal and running: ``` npm install -g @agentpmt/mcp-router agentpmt-setup ``` This will connect you to local agents like Claude Code, Windsurf, Grok Build, Cursor, etc. Alternatively you can connect to the hosted version with this config block, no installation required: ``` { "mcpServers": { "agentpmt": { "type": "streamable-http", "url": "https://api.agentpmt.com/mcp", "headers": { "Authorization": "Bearer ", "x-instance-metadata": "{\"client\":\"generic-mcp\",\"platform\":\"remote\"}" } } } } ``` [View MCP Connection Instructions](/docs/mcp-reference/connection) for more details. ### How do I trigger this workflow? You can use it here in the browser by clicking the 'Try It' button. If you 'star' the workflow it will save to your dashboard for quick access. To use the workflow in an external agent, make sure you have followed the steps to connect it to the MCP server and then copy / paste this prompt, or just tell it to use the AgentPMT MCP server and use this workflow. > Call the AgentPMT-Workflow-Skills tool with action 'get\_workflow\_skill' and skill\_id 698fb9497ad294de3fc0360b ("Route Planner From Address Photos").