OneMap MCP Server v2

A Python-based MCP (Model Context Protocol) server that provides comprehensive access to Singapore's OneMap APIs. Built with FastMCP for easy integration with AI assistants and Microsoft AI Foundry.

Features

This server exposes 35+ tools across 10 API categories:

• Search - Address and location search
• Reverse Geocode - Convert coordinates to addresses (WGS84 and SVY21)
• Routing - Public transport, driving, walking, cycling, barrier-free routes
• Coordinate Converters - EPSG 4326 (WGS84), EPSG 3414 (SVY21), EPSG 3857
• Themes - Access 100+ thematic layers for locations, amenities, boundaries
• Planning Area - Singapore's 55 planning area information
• Population Query - Demographics and statistics by planning area
• Nearby Transport - Find nearby MRT/LRT stations and bus stops
• Static Map - Generate static map images with optional overlays

Prerequisites

• Python 3.11+
• OneMap Account (register at OneMap API)

Installation

Local Development

1. Clone the repository:

cd onemap-mcp

2. Create a virtual environment:

python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

3. Install dependencies:

pip install -r requirements.txt

4. Create .env file with your credentials:

cp .env.example .env
# Edit .env with your OneMap credentials

5. Run the server:

python server.py

Environment Variables

Create a .env file with:

ONEMAP_EMAIL=your_email@example.com
ONEMAP_EMAIL_PASSWORD=your_password

Docker Deployment

1. Build the Docker image:

docker build -t onemap-mcp .

2. Run the container:

docker run -d \
  -e ONEMAP_EMAIL="your_email@example.com" \
  -e ONEMAP_EMAIL_PASSWORD="your_password" \
  --name onemap-mcp \
  onemap-mcp

Available Tools

Search & Geocoding

Tool	Description
search	Search for addresses, buildings, postal codes
reverse_geocode_wgs84	Get address from WGS84 coordinates
reverse_geocode_svy21	Get address from SVY21 coordinates

Routing

Tool	Description
route_walk_drive_cycle	Walking, driving, cycling, barrier-free routes
route_public_transport	Bus and MRT routes with fare info

Coordinate Conversion

Tool	Description
convert_4326_to_3857	WGS84 → Web Mercator
convert_4326_to_3414	WGS84 → SVY21
convert_3414_to_4326	SVY21 → WGS84
convert_3414_to_3857	SVY21 → Web Mercator
convert_3857_to_4326	Web Mercator → WGS84
convert_3857_to_3414	Web Mercator → SVY21

Themes

Tool	Description
get_all_themes_info	List all 100+ thematic layers
get_theme_info	Get info about a specific theme
check_theme_status	Check if theme was updated
retrieve_theme	Retrieve theme data

Planning Areas

Tool	Description
get_all_planning_areas	Get all 55 planning area polygons
get_planning_area_names	List planning area names
get_planning_area_by_location	Get planning area for a location

Population Data

Tool	Description
get_population_age_group	Population by age
get_ethnic_distribution	Ethnic group distribution
get_economic_status	Employment statistics
get_household_monthly_income	Income distribution
get_education_status	Education levels
... and more

Transport

Tool	Description
get_nearby_mrt_stations	Find nearby MRT/LRT stations
get_nearby_bus_stops	Find nearby bus stops

Static Maps

Tool	Description
get_static_map	Generate map images with overlays

Usage Examples

Search for a location

# Search for Marina Bay Sands
result = await search(search_value="Marina Bay Sands")

Get route directions

# Driving route from Changi to Orchard
result = await route_walk_drive_cycle(
    start_lat=1.3644,
    start_lon=103.9915,
    end_lat=1.3048,
    end_lon=103.8318,
    route_type="drive"
)

Find nearby MRT stations

result = await get_nearby_mrt_stations(
    latitude=1.3521,
    longitude=103.8198,
    radius_in_meters=1000
)

Project Structure

onemap-mcp/
├── server.py          # FastMCP server with all tools
├── mcp.json           # MCP manifest
├── tools.json         # Tool definitions for AI Foundry
├── onemap/
│   ├── __init__.py
│   └── utils.py       # HTTP client and utility functions
├── .env               # Your credentials (not in git)
├── .env.example       # Template for credentials
├── Dockerfile
├── requirements.txt
└── README.md

Deployment to Azure

Azure Container Apps

# Build and push to Azure Container Registry
az acr build --registry <registry-name> --image onemap-mcp:latest .

# Deploy to Container Apps
az containerapp create \
  --name onemap-mcp \
  --resource-group <resource-group> \
  --image <registry-name>.azurecr.io/onemap-mcp:latest \
  --env-vars ONEMAP_EMAIL=<email> ONEMAP_EMAIL_PASSWORD=<password>

Microsoft AI Foundry Integration

1. Deploy the server to a publicly accessible endpoint
2. Use the tools.json file to configure tool definitions
3. Configure ONEMAP_EMAIL and ONEMAP_EMAIL_PASSWORD environment variables

License

MIT

Resources

• OneMap API Documentation
• Model Context Protocol
• Microsoft AI Foundry