Drive-Time Plotter MCP

A Model Context Protocol (MCP) server that analyzes traffic patterns throughout the day using Google Maps API, providing fast visual insights and recommendations.

Motivated by the Hugging Face MCP Hackathon - A production-ready MCP server for intelligent commute planning.

What It Does

• Analyzes traffic patterns across 24 hours with 15-minute intervals
• Shows optimistic/pessimistic/average drive time predictions
• Completes full analysis in ~4 seconds using parallel API requests (120x faster than sequential!)
• Works with Claude Desktop, Claude Code, and standalone CLI
• Generates both terminal ASCII plots and route maps

Quick Start

1. Install

python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
pip install -e .

2. Setup API Key

Get your Google Maps API key from https://console.cloud.google.com/apis/credentials

Enable these APIs:

• Geocoding API
• Directions API
• Maps Static API

Create .env file from template:

cp .env.example .env
# Edit .env and add your key:
# GOOGLE_MAPS_API_KEY=your_key_here

3. Test

./test.sh

You should see traffic analysis in ~4 seconds!

---

Usage

Terminal (Fastest)

./test_custom.sh

Edit test_custom.sh to customize:

• Origin/Destination (default: Evans Hall, UC Berkeley → SFO)
• Date
• Time range
• Interval

Or use the CLI directly:

python cli/driveplot_fast.py \
  --origin "Your Home" \
  --destination "Your Work" \
  --date 2025-11-20 \
  --start 06:00 --end 10:00 \
  --interval 15 \
  --ascii --save-map outputs/route.png --yes

As MCP Server with Claude

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "drivetime-plotter": {
      "command": "python",
      "args": ["-m", "mcp_server.server"],
      "env": {
        "GOOGLE_MAPS_API_KEY": "your_key_here"
      },
      "cwd": "/path/to/mcp-hackathon"
    }
  }
}

Restart Claude Desktop. You can now ask Claude: "When should I drive from X to Y?"

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How It Works

For Terminal Users

1. Run ./test_custom.sh
2. Get results in ~4 seconds (parallel API calls)
3. See two outputs:
   • Colored ANSI plot (beautiful terminal visualization)
   • Simple text plot (plain text using +, o, * characters for Claude Code)

For Claude/Claude Code

When you ask "When should I drive from X to Y?":

1. Quick Response (< 10 seconds):

   [Show simple text plot]
   🟢 BEST: 5-7 AM (35 min)
   🔴 WORST: 2-4 PM (60 min)
   💡 Recommendation: Leave before 7 AM
   
   Want more details?
   

2. Detailed Response (if you say yes):

   • Hour-by-hour breakdown
   • Specific scenarios
   • Multiple options

Key AI Behavior

Human-Realistic Recommendations:

• ✅ "Leave 5-7 AM" (reasonable)
• ❌ "Leave 2 AM" (unrealistic for most people - humans need sleep!)

Adapts to Specificity:

• Vague question → Quick answer + ask for more
• Specific constraint → Calculate and provide options
• Flight time → Work backwards with buffer

---

Architecture

File Structure

mcp-hackathon/
├── .env                       # API key (gitignored, copy from .env.example)
├── .env.example               # Template for API key
├── requirements.txt           # Python dependencies
├── setup.py                   # Package setup (enables `pip install -e .`)
├── test.sh                    # Quick smoke test (~2 sec)
├── test_custom.sh             # Main usage script (customizable route)
├── outputs/                   # Generated maps and plots (gitignored)
├── cli/
│   └── driveplot_fast.py      # Fast CLI with parallel requests
└── mcp_server/
    ├── __init__.py            # Makes mcp_server a Python package
    ├── server.py              # MCP server (exposes tools to Claude)
    ├── google_maps.py         # Google Maps API integration
    └── utils.py               # Helper functions (LatLng, minute_grid, etc.)

Why These Files?

Core Files:

• cli/driveplot_fast.py - Standalone terminal tool (works without MCP)
• mcp_server/server.py - MCP server for Claude integration
• mcp_server/google_maps.py - API calls (shared by CLI and MCP)
• mcp_server/utils.py - Shared utilities
• mcp_server/__init__.py - Required for Python package (enables from mcp_server import ...)

Configuration:

• .env - Your API key (never committed to git)
• .env.example - Template for new users
• setup.py - Package metadata and dependencies (needed for pip install -e .)
• requirements.txt - Direct dependencies list

Testing:

• test.sh - Quick verification (1-hour window, ~2 seconds)
• test_custom.sh - Real usage (24 hours, ~4 seconds)

API Key Management

Single Source of Truth:

.env file (GOOGLE_MAPS_API_KEY=...)
  ↓
  ├─→ Shell scripts (loaded via `export $(grep -v '^#' .env | xargs)`)
  └─→ Python code (os.getenv("GOOGLE_MAPS_API_KEY"))

Only mcp_server/google_maps.py defines:

GOOGLE_KEY = os.getenv("GOOGLE_MAPS_API_KEY", "")

All other code imports and uses this variable.

Performance

• Parallel API calls: Up to 30 concurrent requests (first pass)
• Smart retry with while loop: Retries only failed requests with reduced concurrency (10 workers)
• Multiple retry rounds: Up to 3 rounds total, ensures maximum success rate
• Speed: ~4 seconds for full 24-hour analysis (96 data points)
• 120x speedup vs sequential approach

---

MCP Tools Exposed

When running as an MCP server, Claude can use these tools:

1. geocode(query: str)

• Converts address to coordinates
• Returns candidates with formatted addresses and lat/lng
• Example: "Berkeley, CA" → [(37.8715, -122.2730), ...]

2. static_map(origin_lat, origin_lng, dest_lat, dest_lng)

• Generates Google Maps static image URL
• Shows route with markers
• Returns URL to PNG image

3. eta_series(...)

• Gets traffic data across time range
• Returns optimistic/pessimistic/average drive times
• Parameters:
  • origin_lat, origin_lng
  • dest_lat, dest_lng
  • date, start_time, end_time
  • interval_minutes
  • include_plot (optional, for matplotlib PNG in Claude chat)

Google Maps APIs Used

• Geocoding API: Address → Coordinates
• Directions API: Traffic-aware route duration
• Static Maps API: Route visualization

Traffic Models:

• optimistic - Best-case scenario (light traffic)
• pessimistic - Worst-case scenario (heavy traffic)
• Average - Calculated from both (realistic expectation)

---

Output Format

Simple Text Plot (for Claude Code)

 66 min |                                  o
 64 min |                                 o ooo
 62 min |                               oo
 ...
 32 min |        **********************
 30 min | +++++++++++++++++++++++++++++++
        +------------------------------------------------------------
          0   1   2   3   4   5   6   7   8   9   10  11  12  ...
          Hour of Day

LEGEND:
  + = Optimistic  |  o = Pessimistic  |  * = Average
  B = Best time   |  W = Worst time

Features:

• Shows all 24 hours
• Three traffic scenarios
• Marks best/worst times
• Human-readable x-axis (proper spacing for single/double-digit hours)
• No ANSI codes (renders in Claude Code responses)

Colored ANSI Plot (for Terminal)

Same layout but with beautiful colors using plotext library.

---

Troubleshooting

API Errors

"Missing GOOGLE_MAPS_API_KEY" → Check .env file exists and has your key → Make sure you copied from .env.example: cp .env.example .env

"REQUEST_DENIED" → Enable APIs in Google Cloud Console (Geocoding, Directions, Maps Static) → Verify billing is active (you get $200/month free credit)

Performance Issues

Retrying failed queries multiple times → Some API requests failing due to rate limits → Script automatically retries with reduced concurrency → Wait for completion - most queries eventually succeed

Slow (> 10 seconds) → Network issues → Try again later → Default: 30 workers → 10 workers for retries (adjustable in code)

Installation Issues

"Module not found" when running MCP server → Run pip install -e . to install package in editable mode

"Permission denied" on .sh files → Run chmod +x test.sh test_custom.sh

Output files not saved → Check outputs/ folder exists (created automatically) → Verify path in --save-map flag

---

Cost

Very cheap!

• Full 24-hour query (96 points): ~$0.001
• $200/month free credit = ~200,000 queries
• You won't hit limits during development or normal usage

---

For Hackathon Judges

What We Built

A production-ready MCP server for traffic analysis with:

• ✅ 120x speedup (10 min → 4 sec via parallel processing)
• ✅ Beautiful terminal visualizations (dual output: ANSI + plain text)
• ✅ Human-friendly AI behavior (considers sleep/work schedules)
• ✅ Smart retry logic (while loop with multiple rounds, only retries failures)
• ✅ Clean, publishable code (minimal necessary files, comprehensive docs)

Key Innovations

1. Two-tier response system

   • Quick answer first (< 10 sec)
   • Detailed analysis on request
   • Prevents slow, overwhelming responses

2. Human-realistic constraints

   • Don't recommend 2 AM departures
   • Consider work hours, sleep needs
   • Practical time windows

3. Dual output formats

   • Colored ANSI for terminal users
   • Simple text (+, o, *) for Claude Code responses
   • Solves ANSI rendering limitation

4. Robust API handling

   • Parallel requests with ThreadPoolExecutor
   • While loop retry (not just 2 passes)
   • Smart concurrency reduction (30 → 10 workers)
   • Graceful degradation on failures

Track

Track 1: Building MCP

This is a complete, production-ready MCP server that:

• Exposes useful tools (geocode, eta_series, static_map)
• Solves real problems (commute planning, meeting scheduling)
• Works with both Claude Desktop and Claude Code
• Has excellent documentation
• Is ready to publish and use

---

Advanced Usage

Custom Time Range

python cli/driveplot_fast.py \
  --origin "Your Home" \
  --destination "Your Work" \
  --date 2025-11-20 \
  --start 06:00 --end 10:00 \  # Morning only
  --interval 30 \               # Every 30 min
  --ascii --yes

Different Intervals

• 15 min: Detailed analysis (96 data points, ~4 sec)
• 30 min: Balanced (48 points, ~2 sec)
• 60 min: Quick overview (24 points, ~1 sec)

Save Map to outputs/

python cli/driveplot_fast.py \
  --origin "Berkeley, CA" \
  --destination "San Francisco, CA" \
  --date 2025-11-20 \
  --ascii --save-map outputs/my_route.png --yes

---

Security

✅ API key protected:

• Stored in .env (gitignored)
• Never committed to version control
• Single source of truth
• Easy to rotate
• Template provided (.env.example)

✅ No hardcoded secrets anywhere in codebase

✅ Best practices:

• Environment variables via python-dotenv
• Clear separation of code and config
• Comprehensive .gitignore

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Future Improvements

Ideas for extension:

• Add Apple Maps support (already structured for it)
• Historical data tracking (compare traffic patterns over time)
• Calendar integration (auto-suggest departure times)
• Multiple routes comparison (A vs B)
• Web UI with Gradio (for Track 2 submission)

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License

MIT License - use freely!

This is the standard license for MCP servers. Feel free to:

• Use in commercial projects
• Modify and redistribute
• Incorporate into closed-source software

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Credits

Built for the Hugging Face MCP Hackathon (Track 1)

Technologies used:

• FastMCP - MCP server framework
• Google Maps Platform APIs - Geocoding, Directions, Static Maps
• plotext - Terminal plotting
• rich - Beautiful terminal output
• ThreadPoolExecutor - Parallel API requests

---

Questions?

For issues or questions:

1. Check the Troubleshooting section above
2. Verify your .env file is set up correctly
3. Run ./test.sh to verify installation
4. Check that Google Maps APIs are enabled in Cloud Console