# Appointment Scheduling and Route Planner

> Takes a CSV or spreadsheet file with addresses, asks for a starting drive time, time per stop, and starting address, then parses the addresses, optimizes the driving route, calculates estimated arrival and departure times for each location, and generates a CSV with the full schedule. Returns the optimized route map, Google Maps directions link, and the schedule CSV both locally and via notification. Ideal for field sales, service technicians, delivery planning, or any multi-stop appointment scheduling.

Content type: workflow
Source URL: https://www.agentpmt.com/agent-workflow-skills/appointment-scheduling-and-route-planner
Markdown URL: https://www.agentpmt.com/api/agent/workflows/appointment-scheduling-and-route-planner?format=agent-md
Updated: 2026-03-27T04:01:49.795Z
Author: firef1ie

---

Estimated time saved: 45 minutes.

## Tools

- File To JSON Parsing
- Multi-Location Route Optimizer W Map
- Get Users Current Time / Date
- Date and Time Calculator
- Web Data Convertor
- File Management
- AgentPMT Send Human Request

## Workflow Outline

1. Parse Uploaded Spreadsheet: Parse the user's uploaded CSV or spreadsheet file containing addresses. Convert the file contents to JSON format so that all rows and columns are accessible as structured data. Ac...
2. Extract Addresses and Parameters: Goal: Extract all addresses from the parsed spreadsheet data and collect the user's scheduling parameters | Inputs: Parsed JSON data from the spreadsheet. The user should also provide: starting address, starting drive t...
3. Optimize Route With Map: Use the multi-location route optimizer to find the optimal driving route through all destination addresses, starting from the user's specified starting address. Enable round trip...
4. Get User Timezone: Get the user's current date, time, and timezone. This will be used to ensure all calculated arrival and departure times are displayed in the user's local timezone.
5. Plan Stop Schedule: Goal: Using the optimized route order and travel times, prepare a sequential list of stops with the time calculation data needed for each one, including the return trip to the starting address | Inputs: Optimized round-...
6. Calculate Time For Each Stop: Repeat this section for each stop. Iterate over each stop in the planned schedule in route order, including the final return-home entry. For each stop, use the Date and Time...
7. Calculate Arrival and Departure Time: For the current stop, calculate two times: 1) ARRIVAL TIME - Take the previous stop's departure time (or the user's starting drive time if this is the first stop) and add the driv...
8. Compile Route Schedule Data: Goal: Compile all calculated arrival and departure times with the original spreadsheet data into a structured JSON array ready for CSV conversion, including the return-home leg | Inputs: All stop data with calculated ar...
9. Convert Schedule to CSV: Convert the JSON array of route schedule data to CSV format. The JSON contains stop numbers, original spreadsheet fields, arrival times, departure times, and drive times for each...
10. Store CSV File in File Management: Upload the generated CSV file with File Management using action 'upload_standard' and a descriptive filename like 'optimized_route_schedule.csv'. Set expiration to 7 days if suppo...
11. Send Results to User: Send the complete route planning results to the user as a notification (request_type: notification_only). Include: 1) A summary of the optimized round-trip route with the number o...

## 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 <AGENTPMT_BEARER_TOKEN>",
        "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 698d4aaca0d2109d78fc9b4c ("Appointment Scheduling and Route Planner").