# Luhn CC Validator MCP > Luhn CC Validator is an MCP Server that instantly verifies credit card numbers using the mathematical Luhn algorithm. It stops your AI client from sending fake or mistyped payment data to external gateways like Stripe. The tool checks for mathematical validity and detects the card brand (Visa, Amex, etc.) before you spend API credits on failed transactions. ## Overview - **Category:** developer-tools - **Price:** Free - **Tags:** checksum-validation, fraud-prevention, credit-card-validation, data-integrity, algorithmic-check ## Description When you're building agents that handle money—any agent—you gotta deal with messy inputs. Your AI client is great at language, sure, but it can't run complex math; if it gets payment details wrong, or if it hallucinates a number, you’ve got a problem. That bad data hits your payment gateway, wastes API credits, and flags your entire system for potential fraud. The `validate_luhn` tool fixes that right at the edge of your workflow. It instantly verifies credit card numbers using the established mathematical Luhn algorithm. Before your agent sends anything to external processing services like Stripe or Adyen, you run this check. You're not just checking if the number is long enough; you're checking its fundamental integrity. This tool accepts a raw card number string and performs two distinct checks: it determines mathematical validity using the Luhn modulo-10 checksum, and it identifies the associated brand based on known prefix rules. If the math fails, the process stops immediately with an error code. You don't waste time or money processing invalid data. The core function here is simple but critical: applying the Luhn algorithm. This isn't some basic length check; it’s a mathematically rigorous checksum formula used globally to detect transcription errors in number sequences. The tool processes that raw card number string you give it, running the full validation cycle. If the number fails this deep mathematical test, your agent gets an immediate error telling it why. On the other hand, if the math passes—meaning the sequence of digits is mathematically sound according to Luhn's rules—the tool reports that status and simultaneously identifies what card brand the prefix claims to be. This means you get both a pass/fail status *and* confirmation of the type (Visa, Amex, Mastercard) based purely on the starting digits. Think about it: most basic input validators just check for numbers or maybe a certain length. They don't care if that number sequence could actually exist in the real world. This MCP ensures that when your agent thinks it has processed a payment identifier, you know two things: first, that the string of digits is mathematically plausible; and second, what kind of card it represents. You use this capability to stop transactions before they even hit the main gateway queue. It’s how you keep your API usage clean and predictable. Instead of letting your agent send fifty failed payments that burn through your credit limits, you let it run `validate_luhn` first. It'll tell you right away if those five numbers are bogus before they ever touch the external network. This saves money and keeps your fraud scores low. The tool’s output gives you a clear, actionable status: whether or not the number passes the checksum, and which brand it matches according to industry-standard prefix detection. You're building reliability into the payment path itself. Your agent doesn't have to guess; it just asks this server for confirmation. It gets the answer, and then it proceeds with confidence. ## Tools ### validate_luhn Pass a card number string to check its mathematical validity using the Luhn algorithm and detect the associated brand (Visa, Mastercard, Amex). ## Prompt Examples **Prompt:** ``` Run the Luhn algorithm to check if `4242424242424242` is a mathematically valid credit card number. ``` **Response:** ``` ✅ **Checksum Valid:** Passed Luhn verification. Brand identified as `Visa` based on prefix rules. ``` **Prompt:** ``` A user submitted `378282246310005`. Verify the checksum and detect if it is American Express. ``` **Response:** ``` ✅ **Validation Status:** Valid. - **Brand:** `American Express` - **Sanitized:** Cleaned spaces and hyphens successfully. ``` **Prompt:** ``` Validate this mistyped card number `5555444433332221` before sending it to the Stripe API. ``` **Response:** ``` ❌ **Pre-flight Error:** Blocked! The number failed the mathematical Luhn modulo-10 checksum. ``` ## Capabilities ### Validate Checksum The tool determines if a given card number passes the mathematical Luhn modulo-10 checksum. ### Detect Card Brand It identifies the card's brand (e.g., Visa, Mastercard) based purely on the prefix digits of the provided number. ## Use Cases ### Handling New User Signups A user signs up via a chatbot and provides their payment details. Instead of blindly passing the numbers, your agent first calls `validate_luhn`. If the check fails, the agent immediately tells the user to re-enter the number, preventing a costly failed transaction attempt. ### Batch Data Cleanup You're migrating old customer records where payment details might be dirty. Your workflow runs through a list of numbers and passes each one to `validate_luhn`. The agent collects only the mathematically valid records, building a clean dataset for payment processing. ### Webhook Processing A payment gateway sends an event webhook with card data. Before your internal system processes it and triggers fulfillment logic, you run `validate_luhn` on the incoming number to confirm its integrity, ensuring the data is trustworthy. ### Payment Intent Generation When a user confirms purchase details in an AI conversation, your agent doesn't proceed until it passes the card number through `validate_luhn`. This ensures that when the final payment intent call hits the API, the data is guaranteed to pass basic checksum checks. ## Benefits - Saves API credits. You block mathematically invalid card numbers *before* your agent attempts a costly call to Stripe or Adyen, saving money and reducing rate limiting risk. - Reduces fraud alerts. By catching obvious typos (like `555...1` instead of `555...2`), you keep your system clean and avoid false positives in anti-fraud monitoring. - Accurate brand detection. It tells you if the number is a Visa or an Amex just by checking the prefix, giving your agent context it needs for downstream processing logic. - Zero latency guardrail. This validation runs at the edge of the workflow, meaning the check happens immediately when needed—no slow database lookups required. - Simple integration. Your AI client calls `validate_luhn` using a single, clean tool call. You don't need to write complex regex or implement the algorithm yourself. ## How It Works The bottom line is: it acts as an immediate guardrail, ensuring payment data is mathematically sound before your code proceeds to expensive external API calls. 1. Your AI client sends a raw credit card number string to the `validate_luhn` tool. 2. The server executes the Luhn algorithm, checking the number's mathematical integrity against established checksum rules and detecting the brand prefix. 3. You receive a structured response that confirms validation status (Valid/Invalid) and lists any identified brand. ## Frequently Asked Questions **Does Luhn CC Validator check if a card number exists?** No, it only checks mathematical integrity. `validate_luhn` confirms if the number follows the rules of the checksum and brand prefix, but it can't confirm if the bank account is active or real. **How do I use validate_luhn with my AI agent?** You simply add `validate_luhn` as a tool to your agent's available functions. When the user inputs payment details, you program the flow to call this tool first. **Is Luhn CC Validator only for Visa cards?** No. The tool is designed to detect multiple major brands—Visa, Mastercard, Amex, and Discover—by reading the prefix digits and running the universal checksum check. **What if my payment gateway accepts invalid numbers sometimes?** Even if your gateway *can* accept bad data, you shouldn't rely on that. Using `validate_luhn` acts as a mandatory pre-flight guardrail to maintain data integrity and save operational costs. **What is the latency when calling validate_luhn?** The validation process runs at zero latency because it executes on the edge. This means you get instant results without waiting for external API calls, letting your agent move faster. **Does Luhn CC Validator handle sensitive payment data securely?** Yes. The tool validates numbers mathematically and never stores or transmits raw card details outside of the request/response cycle. It's designed for high-integrity, zero-persistence checks. **How does validate_luhn handle non-numeric input formats?** It's robust. Before running the Luhn check, it automatically cleans and sanitizes your input by removing common separators like spaces or hyphens. This lets you pass data in any readable format. **What are the requirements for connecting Luhn CC Validator to a new agent client?** Because it uses Model Context Protocol (MCP), compatibility is built-in. As long as your AI client supports MCP, you just need to route the card number data through the tool endpoint. **Does it process payments?** No, it purely validates the mathematical checksum of the number. It does not contact any bank. **Is it secure?** Yes, 100% local evaluation inside the edge worker memory. No network requests are made. **What brands are supported?** Visa, Mastercard, American Express, and Discover are instantly identified.