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HUD User (USPS Crosswalk)

HUD User (USPS Crosswalk) MCP for AI. Map any US ZIP code to its official Census boundary.

Claude Claude
ChatGPT ChatGPT
Cursor Cursor
Gemini Gemini
Windsurf Windsurf
VS Code VS Code
JetBrains JetBrains
Vercel Vercel
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HUD User (USPS Crosswalk) MCP on Cursor AI Code EditorHUD User (USPS Crosswalk) MCP on Claude Desktop AppHUD User (USPS Crosswalk) MCP on OpenAI Agents SDKHUD User (USPS Crosswalk) MCP on Visual Studio CodeHUD User (USPS Crosswalk) MCP on GitHub Copilot AI AgentHUD User (USPS Crosswalk) MCP on Google Gemini AIHUD User (USPS Crosswalk) MCP on Lovable AI DevelopmentHUD User (USPS Crosswalk) MCP on Mistral AI AgentsHUD User (USPS Crosswalk) MCP on Amazon AWS Bedrock

Connect to your AI in seconds.

HUD User (USPS Crosswalk) MCP maps US ZIP codes to official Census Bureau boundaries. It provides crosswalks linking a simple 5-digit ZIP code to complex geographies like Tracts, Counties, CBSAs, and Congressional Districts.

This is essential for accurate data processing in real estate, urban planning, or demographic research.

What your AI can do

Cbsa to zip

Finds all the ZIP codes that belong within a specific Core Based Statistical Area (CBSA).

Cbsadiv to zip

Retrieves all ZIP codes contained in a given CBSA Division.

Cd to zip

Maps out every ZIP code located within a specific Congressional District.

+ 7 more capabilities included
Map ZIP codes to county boundaries

Determines the precise county and Census Tract associated with any given five-digit ZIP code.

Cross-reference large geographic areas

Maps major statistical regions, like CBSAs or Congressional Districts, back to their corresponding ZIP codes.

Identify demographic boundaries

Links a specific ZIP code to its underlying Census Bureau divisions (CBSA Divisions and Tracts).

Calculate state-level data points

Retrieves county, district, or tract information necessary for high-level planning and reporting.

Included with Plan

Waiting for input…

AI Agent

HUD User (USPS Crosswalk) with 10 Tools

These ten tools allow you to cross-reference US ZIP codes against every major Census Bureau boundary type—from tracts up through Core Based Statistical Areas.

Make your AI actually useful.

Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.

Start using HUD User (USPS Crosswalk) on Vinkius

Cbsa To Zip

Finds all the ZIP codes that belong within a specific Core Based Statistical Area (CBSA).

Cbsadiv To Zip

Retrieves all ZIP codes contained in a given CBSA Division.

Cd To Zip

Maps out every ZIP code located within a specific Congressional District.

County To Zip

Lists all the ZIP codes that are part of a specified county.

Tract To Zip

Finds every ZIP code associated with a specific Census Tract.

Zip To Cbsa

Determines which Core Based Statistical Area (CBSA) a given ZIP code belongs to.

Zip To Cbsadiv

Maps a specific ZIP code to its corresponding CBSA Division.

Zip To Cd

Looks up the Congressional District that encompasses an input ZIP code.

Zip To County

Maps a specific ZIP code directly to its county name and ID.

Zip To Tract

Identifies the precise Census Tract boundaries for any given ZIP code.

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Claude AI

Claude AI

1

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.

2

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.

3

Start a conversation

Open a new chat. The HUD User (USPS Crosswalk) integration is available immediately — no restart needed.

Choose How to Get Started

Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.

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Works with Claude, ChatGPT, Cursor, and more

The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.

This connection provides 10 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.

Manually linking address data to official boundaries is a nightmare.

Think about it. You've got your list of ZIP codes—maybe thousands of them. To run a proper analysis, you need more than just the zip code; you need to know what county they fall in, which Congressional District governs them, and what Census Tracts are active there. Today, that means jumping between three or four different government websites, running separate searches for each boundary type, and then spending hours copy-pasting IDs into a master spreadsheet just to align the data.

With this MCP, you feed your AI client one list of ZIP codes. It handles all those complicated lookups behind the scenes. Instead of messy spreadsheets and manual reconciliation, you get one clean output: a structured dataset that links every single input code to its associated county, tract, CBSA, and district boundaries.

You'll gain precise jurisdictional data with HUD User (USPS Crosswalk) MCP

Specific manual steps that disappear? The tedious task of cross-referencing CBSA Divisions; you just call `zip_to_cbsadiv`. You don't have to manually map a zip code against dozens of regional planning documents anymore. Similarly, linking the ZIP to its specific Census Tract is now instant via `zip_to_tract`.

What’s different? Your data isn't just 'location-aware,' it's *jurisdictionally verified*. You can start your analysis immediately because all the necessary geographic context—the county from `zip_to_county`, the district from `zip_to_cd`, and everything else—is correlated in one pass.

What your AI can actually do with this

When you're working with location data, the biggest headache isn't getting the address; it’s figuring out which official boundaries that address actually falls into. A ZIP code is just a simplification, right? But for proper analysis—whether you're running market predictions or modeling demographic shifts—you need precision. This MCP connects to the HUD User Data API and gives your AI client all the necessary crosswalks in one place.

You can map ZIP codes back to everything from Census Tracts and Counties to Core Based Statistical Areas (CBSAs) and even Congressional Districts.

It's about going beyond the simple zip code look-up. If you need to analyze how certain urban areas correlate with county lines, or if you’re building a real estate tool that needs district-level data, this MCP handles the heavy lifting of geography. You can connect it through Vinkius and let your agent pull in all these official mapping layers without having to piece together ten different government APIs.

It's raw power for people who need clean, reliable spatial data.

Built · Hosted · Managed by Vinkius HUD User Crosswalk - Map ZIP Codes to Census Data
Server ID 019d75b4-cd12-71da-afb7-72ebfc28088c
Vinkius Inspector
Compliance Grade A+
Score 98.33/100
Vinkius Inspector Badge — Score 98.33/100

Questions you might have

How do I map ZIP codes to Census Tracts using the `zip_to_tract` tool? +

The MCP finds the precise Census Tract for any given ZIP code. You simply input your list of ZIP codes, and the tool returns the specific tract boundary data needed for granular analysis.

What is the difference between `zip_to_county` and `cbsa_to_zip`? +

zip_to_county takes a ZIP code and tells you its single county. Conversely, cbsa_to_zip takes an entire Core Based Statistical Area (CBSA) and gives you every ZIP code that belongs to it.

Can I find all the CBSAs from one zip code using `zip_to_cbsa`? +

Yes, running zip_to_cbsa directly maps the input ZIP code to its corresponding Core Based Statistical Area. This is a key step for broad market analysis.

Does `county_to_zip` work in reverse of `zip_to_county`? +

Yes, it does. If you know the county name or code and need all associated ZIPs, use county_to_zip. This is useful for generating full lists for a region.

Before running `county_to_zip`, what authentication steps are needed? +

You need an API key provided by HUD User. The MCP handles standard OAuth flows, securing access to all the crosswalk data points you request.

If I process thousands of ZIP codes using `zip_to_tract`, are there rate limits? +

Yes, the underlying API imposes standard request throttling. For bulk processing, batching your requests or checking the HUD User developer documentation for specific commercial quotas is necessary.

When running `zip_to_cd`, what happens if a ZIP code isn't assigned to a congressional district? +

The tool returns null or an error message indicating no match. Always check the returned data for empty values before processing those results in your application logic.

Can `cbsa_to_zip` provide demographic information, or just mapping? +

This MCP is strictly a crosswalk tool; it only maps the geographic relationship. You receive the list of associated ZIP codes but must query other external services for population or income metrics.

How do I get a HUD User Access Token? +

Register for an account at the HUD User API page (https://www.huduser.gov/portal/dataset/uspszip-api.html), confirm your email, and generate a token in your user dashboard.

Which year of data is used? +

By default, the API returns the most recent available data. You can optionally specify a year and quarter in each tool.

Does it support mapping Tracts back to ZIP codes? +

Yes, tools like tract_to_zip and county_to_zip allow bidirectional crosswalking between geography IDs and ZIP codes.

Built & Managed by Vinkius 30s setup 10 tools

We've already built the connector for HUD User (USPS Crosswalk). Just plug in your AI agents and start using Vinkius.

No hosting. No infrastructure. No complex setup.
All 10 tools are live and waiting. You're up and running in seconds.

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