Luhn CC Validator MCP for AI. Stop sending bad credit card numbers to payment APIs.

Q: Does Luhn CC Validator check if a card number exists?

No, it only checks mathematical integrity. validateluhn 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.

Q: How do I use validateluhn with my AI agent?

You simply add validateluhn as a tool to your agent's available functions. When the user inputs payment details, you program the flow to call this tool first.

Q: What if my payment gateway accepts invalid numbers sometimes?

Even if your gateway can accept bad data, you shouldn't rely on that. Using validateluhn acts as a mandatory pre-flight guardrail to maintain data integrity and save operational costs.

Claude

ChatGPT

Cursor

Gemini

Windsurf

VS Code

JetBrains

Vercel

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

Connect to your AI in seconds.

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.

What your AI can do

Validate luhn

Pass a card number string to check its mathematical validity using the Luhn algorithm and detect the associated brand (Visa, Mastercard, Amex).

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.

Ask an AI about this

Included with Plan

Waiting for input…

AI Agent

Luhn CC Validator: 1 Tool for Payment Data Integrity

This single tool allows you to run the Luhn algorithm and detect card brands, ensuring any credit card number processed by your agent is mathematically sound.

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 Luhn CC Validator on Vinkius

Validate Luhn

Pass a card number string to check its mathematical validity using the Luhn algorithm and detect the associated brand (Visa, Mastercard...

Security and governance baked right in.

Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.

Claude AI

Open Claude Settings

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

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.

Start a conversation

Open a new chat. The Luhn CC Validator integration is available immediately — no restart needed.

Antigravity

Configure Agent Environment

Open your Antigravity agent's workspace configuration or mcp-servers.json file.

Bind the Endpoint

Add the Vinkius endpoint URL to your agent's MCP connections list:

"mcp_servers": {
  "luhn-cc-validator": {
    "serverUrl": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
  }
}

Provide your secure token in place of [YOUR_TOKEN_HERE] to ensure your agent requests are authenticated.

Execute

Start your Antigravity session. The agent will autonomously discover and utilize the Luhn CC Validator tools with full Vinkius guardrails applied.

VS Code Copilot

⚡

One-Click Install (Recommended)

In your Vinkius Dashboard, simply click the Add to VS Code button for this server. We'll automatically configure your local workspace.

Or configure manually

Open MCP Settings

Open VS Code, press Ctrl/Cmd + Shift + P, and search for GitHub Copilot: MCP Servers.

Add Server Config

Add the Vinkius endpoint configuration to your mcp-servers.json file:

"luhn-cc-validator": {
  "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
}

Ensure you replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.

LangChain

Install Dependencies

Install the LangChain MCP adapters for your environment:

pip install langchain-mcp-adapters

Connect the Server

Use the SSEClient in LangChain to connect to the Vinkius managed endpoint:

from langchain_mcp_adapters.client import SSEClient

# Connect to Vinkius
client = SSEClient(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
tools = client.get_tools()

CrewAI

Define the Tool

Load the Vinkius MCP tools into your CrewAI agents:

from crewai import Agent
from mcp_crewai import MCPTool

# Connect securely to Vinkius
vinkius_tools = MCPTool(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

# Assign to Agent
researcher = Agent(
    role='Data Researcher',
    tools=vinkius_tools.get_all()
)

Execute Task

Run your CrewAI process. The agent will autonomously route tasks to the Vinkius managed server.

Choose How to Get Started

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

Build Your Own

Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.

Import from OpenAPI, Swagger, or YAML specs
Create Agent Skills with progressive disclosure
Deploy to edge with MCPFusion framework
Built in DLP, auth, and compliance on every call
Real time usage dashboard and cost metering
Publish to catalog or keep private

Start building

Make Your AI Do More

Start with Luhn CC Validator, then connect any of our 5,100+ other servers whenever your AI needs more. One click, no limits.

Use this MCP plus 5,100+ others, all in one place
Add new capabilities to your AI anytime you want
Every connection is secured and compliant automatically
Track usage and costs across all your servers
Works with Claude, ChatGPT, Cursor, and more
New servers added to the catalog every week

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Edge Logic. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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

Sending payment details is fragile. You shouldn't have to manually audit every input.

Today, validating card numbers feels like a multi-step manual process. Your agent collects the data; then, your backend has to run multiple checks: Is it 16 digits? Does it start with 4? Then, you might have to write complex regex and manually implement the Luhn algorithm—a huge maintenance headache that costs development time.

With this MCP Server, the process is instant. Your agent calls `validate_luhn`, passes the raw number, and gets a definitive status back in milliseconds. You stop writing validation logic and start focusing on business outcomes.

Luhn CC Validator: Guarantee clean data before hitting Stripe.

The biggest time sink is the debugging cycle. You send bad data to the payment API, it fails with a generic 'Invalid Card' error, and now you have to backtrack through logs to figure out if the failure was due to length, format, or mathematical checksum.

Now, `validate_luhn` catches that mistake at step zero. It gives you the specific reason—it failed Luhn validation—before any money is spent or rate limits are approached. That’s where the value is.

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What your AI can actually do with this

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.

Built · Hosted · Managed by Vinkius Luhn CC Validator MCP Server - Check Card Numbers

Server ID 019e38ba-fcb7-701c-a74d-ad16ab8f03c9

Vinkius Inspector

Compliance Grade A+

Score 100/100

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Here's how it actually 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.

Your AI client sends a raw credit card number string to the validate_luhn tool.

The server executes the Luhn algorithm, checking the number's mathematical integrity against established checksum rules and detecting the brand prefix.

You receive a structured response that confirms validation status (Valid/Invalid) and lists any identified brand.

Who is this actually for?

This is for the backend developer who can't afford failed Stripe calls. It’s for the FinOps engineer tracking unnecessary cloud spend on bad data, and any platform architect building payment flows into an agent workflow. If your product touches payments, you need this.

Backend Developer

They use validate_luhn in middleware functions to validate incoming webhook or form data before saving records.

FinOps Engineer

They implement this tool to measure and reduce the number of failed API calls, directly lowering cloud costs associated with payment attempts.

Fraud Analyst

They integrate it into monitoring systems to create a first-line defense against obvious data entry errors that might trigger false fraud alerts.

What Changes When You Connect

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.

See it in action

01 01

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.

02 02

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.

03 03

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.

04 04

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.

The honest tradeoffs

Relying only on regex length checks

Anti-pattern

The agent sees a 16-digit string and assumes it's valid because the pattern matches. It then sends this number to Stripe, which rejects it due to bad checksumming.

The Fix

Don't just check length. Always pass the suspect number through validate_luhn. This tool performs the mathematical Luhn modulo-10 check—that's what actually confirms validity.

Using general purpose validation tools

Anti-pattern

Some generic validators might catch obvious misformatting but won't perform the specific checksum math required for credit cards.

The Fix

This tool is built specifically for card data. Use validate_luhn to confirm both the structure and the deep mathematical integrity of the number.

Assuming LLMs can handle validation

Anti-pattern

The developer writes, 'Just ask the AI to validate this.' The agent replies with a non-committal guess or hallucinated confirmation.

The Fix

Never trust the LLM on financial math. You must hardwire validate_luhn into your workflow as an explicit pre-flight tool call.

Questions you might have

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.

Connect to your AI in seconds.

Validate luhn

Luhn CC Validator: 1 Tool for Payment Data Integrity

Make your AI actually useful.

Validate Luhn

Security and governance baked right in.

Claude AI

Open Claude Settings

Add Custom Connector

Start a conversation

Claude Code

Open your terminal

Add the MCP Server

Start coding

Cursor

One-Click Install (Recommended)

Open Cursor Settings

Add New Server

Use in Composer

Antigravity

Configure Agent Environment

Bind the Endpoint

Execute

VS Code Copilot

One-Click Install (Recommended)

Open MCP Settings

Add Server Config

Windsurf

One-Click Install (Recommended)

Open Windsurf Settings

Add Server Endpoint

LangChain

Install Dependencies

Connect the Server

CrewAI

Define the Tool

Execute Task

Choose How to Get Started

Build Your Own

Make Your AI Do More

Works with Claude, ChatGPT, Cursor, and more

Sending payment details is fragile. You shouldn't have to manually audit every input.

Luhn CC Validator: Guarantee clean data before hitting Stripe.

What your AI can actually do with this

Here's how it actually works

Who is this actually for?

What Changes When You Connect

See it in action

Handling New User Signups

Batch Data Cleanup

Webhook Processing

Payment Intent Generation

The honest tradeoffs

Relying only on regex length checks

Using general purpose validation tools

Assuming LLMs can handle validation

When It Fits, When It Doesn't

Questions you might have