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FastMCP server for Australian postcodes and suburbs lookup with fuzzy matching
Configuration
View docs{
"mcpServers": {
"jezweb-australian-postcodes-mcp": {
"command": "fastmcp",
"args": [
"run",
"/path/to/australian-postcodes-mcp/src/server.py"
]
}
}
}This MCP server delivers Australian postcode and suburb data with smart search features, enabling fast, accurate responses for customer service and AI assistants. It combines postcode-to-suburb lookups, fuzzy and phonetic search, autocomplete, radius-based geography, and sensible fallbacks to help users quickly find the right location information.
You connect to the MCP server with an MCP client and issue a range of location-focused queries. Typical tasks include finding all suburbs for a given postcode, locating postcodes for a suburb, validating suburb–postcode pairs, and listing all suburbs within a Local Government Area (LGA). You can also leverage fuzzy matching and phonetic search to handle typos or misheard names, and use geographic search to discover nearby suburbs within a radius.
Common queries you can perform include:
For example, you can use fuzzy or phonetic search to handle misspellings or misheard names, and you can request autocomplete suggestions when you start typing a suburb. If an exact match isn’t found, the system will offer smart alternatives to help you stay productive.
Prerequisites: ensure you have Python installed and a working internet connection. You will also use the FastMCP command-line tool to run the local MCP server.
Step-by-step installation and setup you can follow locally:
Clone or download the project, then install dependencies and import the data used by the server.
Install Python dependencies from the requirements file
Import postcode data into the runtime environment
Test locally with the runtime command to start a development MCP server
Run the local server in development mode using FastMCP
Alternatively, run the production server directly with Python
Deployment can be done via FastMCP Cloud or locally. FastMCP Cloud provides a streamlined workflow to publish and manage the MCP server, while local development uses the standard Python runtime and the FastMCP toolchain for testing.
Find suburbs associated with a given postcode. Returns all matching suburbs for the specified postcode.
Find postcodes associated with a given suburb, optionally filtered by state or region.
Verify that a suburb and postcode pairing is valid and exists in the dataset.
Smart search that accepts either a postcode or a suburb and returns relevant location details.
Suggest closest suburb matches for misspelled inputs with confidence scores.
Provide completions for partial suburb names to speed up data entry.
Suggest spelling corrections for suburb names based on the dataset.
Handle phonetic variations of suburb names to account for mishearing.
Return all suburbs within a specified Local Government Area.
Identify the LGA or city for a given suburb.
Find suburbs within a geographic radius of a given location.
Retrieve suburbs that are adjacent or in close proximity to a given suburb.
Provide counts of postcodes and suburbs grouped by state.
List all available Local Government Areas in the dataset.
Query data by statistical region or SA3/SA4 areas.