# Deterministic Global Postal Formatter MCP for AI Agents MCP > The Deterministic Global Postal Formatter automatically validates and standardizes international postal codes for any data pipeline. It enforces strict, region-specific rules—like adding hyphens to Brazilian CEPs or spaces to UK Postcodes—ensuring your address records are always clean and compliant. ## Overview - **Category:** productivity - **Price:** Free - **Tags:** regex, data-validation, address-formatting, crm-data, localization ## Description Messy customer data is a huge drag on any system. When you're dealing with international addresses, regional quirks kill accuracy. A simple AI model might guess at a ZIP code but struggle when it comes to knowing that a Brazilian CEP needs a hyphen (`01311-000`) or that the UK Postcode requires a strategic space (`SW1A 1AA`). This MCP solves those structural problems by running validation through strict, deterministic regex engines. It doesn't guess; it checks against known global rulesets for Brazil, the US, the UK, and Canada. It takes raw inputs—whether they are missing hyphens or just run together—and automatically formats them perfectly according to local compliance standards. This makes your data immediately usable in CRMs or billing systems without manual cleanup. Since Vinkius hosts this MCP as part of its catalog, you connect it once from any AI client and gain access to reliable address standardization for all your global projects. ## Tools ### format_postal_code Validates and reformats global postal codes by accepting a raw code string and an ISO 2-letter country code to ensure compliance with local standards. ## Prompt Examples **Prompt:** ``` I need to fix 50 customer records. I've got a mix of US ZIP codes and Brazilian CEPs, all mixed up. ``` **Response:** ``` Here’s the cleanup report: * **Record 1 (US):** Input: `90210`. Status: Valid. * **Record 2 (BR):** Input: `1311000`. Status: Valid. Formatted to `01311-000`. * **Record 3 (UK):** Input: `sw1a1aa`. Status: Valid. Formatted to `SW1A 1AA`. * **Record 4 (US):** Input: `123`. Status: Invalid. US ZIP requires at least 5 digits. ``` **Prompt:** ``` Does 'CA90210' look like a valid address component for Canada? ``` **Response:** ``` **Validation Check: Canadian Postcode** * Input Code: `CA90210` * Country Detected: CA (Canada) * Structural Validation: Failed. * Reasoning: The format requires a space separating the letters and numbers, and this input is missing that structure. Please try formatting it as 'V5K 0A1'. ``` **Prompt:** ``` I have a bunch of old data with inconsistent postal codes for Brazil. Can you standardize them? ``` **Response:** ``` **Brazilian CEP Standardization Report** Please provide the raw code and confirm country='BR'. Here are some examples: * Raw: `01311000` -> **Formatted:** `01311-000` (Success) * Raw: `75010123` -> **Formatted:** `75010-123` (Success) * Raw: `AABBCCDD` -> **Validation Error:** CEP must be 8 digits long. ``` ## Capabilities ### Standardize International Postal Formats It takes raw postal codes (like 'sw1a1aa') and instantly reformats them into the correct, compliant structure ('SW1A 1AA'). ### Validate Structural Integrity The MCP rejects addresses that are structurally impossible for their region, providing a clear reason why the data fails validation. ### Handle Multi-Country Data Sets It applies distinct rulesets for four major international regions: Brazil (CEP), United States (ZIP/ZIP+4), United Kingdom, and Canada. ## Use Cases ### Cleaning up imported lead lists A sales operations team imports 10,000 new leads from a global source. Instead of having to write complex regex rules for every country, they run the entire list through the Deterministic Global Postal Formatter MCP using format_postal_code. The result is a clean dataset where all postal codes are standardized and ready for immediate CRM entry. ### Verifying shipping addresses before checkout An e-commerce platform needs to validate the customer's entered address right at the payment stage. They call the MCP, which quickly checks if a US ZIP code is 5 or 9 digits and validates that UK postcode structure, preventing failed shipments. ### Migrating historical CRM data A company acquires another business with decades of dirty customer records. They use the MCP to systematically run every postal code through format_postal_code (e.g., for 'BR' or 'US') before migrating, ensuring the new system doesn't inherit old formatting errors. ### Processing international payroll data The HR team receives salary records from multiple countries. They use the MCP to validate the associated regional codes (like CEP for Brazil) against strict rules, ensuring that all location identifiers are correct before payment processing begins. ## Benefits - Eliminate structural errors: Instead of having to manually spot which ZIP codes are wrong, the format_postal_code tool instantly flags invalid data and tells you why. - Guaranteed compliance: Don't worry about regional differences again. The MCP enforces local standards for everything from Brazilian CEP hyphens to UK spacing. - Saves time on cleanup: It handles messy inputs—like codes run together (`01311000`)—and automatically cleans them into perfectly formatted strings, saving hours of manual data scrubbing. - Faster pipelines: Because it uses pure JS runtime execution, the formatting happens in microseconds without relying on massive external geolocation databases. - Robust validation: You get more than just a pass/fail. The system returns clear diagnostic reports detailing exactly what's wrong with your address component. ## How It Works The bottom line is you get guaranteed compliance. Instead of just guessing an format, your AI client gets back data that's been mathematically verified against global postal standards. 1. You provide the MCP with a raw postal code string and its corresponding two-letter country code. 2. The Deterministic Global Postal Formatter executes the input against strict, deterministic regex rulesets for that specific country. 3. It returns either the perfectly formatted, validated address code or a detailed report explaining exactly why the original input failed validation. ## Frequently Asked Questions **How can I use the Deterministic Global Postal Formatter to clean up my global customer list?** You run your data through this MCP by providing the raw postal code and its country. It automatically validates every entry against strict rules, guaranteeing that all hyphens, spaces, and digit counts are correct before you save or export the cleaned data. **Does Deterministic Global Postal Formatter handle US ZIP+4 codes?** Yes. It supports both standard 5-digit US ZIPs and the full 9-digit format (ZIP+4). If the input is structurally invalid, it will report that failure to you. **Is this MCP reliable for multiple countries like Brazil and the UK?** It's built specifically for reliability. The system uses separate rulesets for each country—for example, knowing the difference between a Brazilian CEP structure and a UK Postcode spacing—making it highly accurate across regions. **What kind of data is too messy for Deterministic Global Postal Formatter?** It struggles if you mix country codes or provide ambiguous input. You must always give the MCP both the raw postal code and the correct two-letter ISO country code to ensure accurate processing. **Can I use this formatting tool in my existing AI agent workflows?** Absolutely. By connecting it via Vinkius, your AI client can call the MCP as a function. This means you write a simple instruction like 'Format this address' and let the MCP handle all the complex logic behind the scenes.