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Mastercard MCP Server for LlamaIndex 12 tools — connect in under 2 minutes

Built by Vinkius GDPR 12 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Mastercard as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

Vinkius supports streamable HTTP and SSE.

python
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to Mastercard. "
            "You have 12 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Mastercard?"
    )
    print(response)

asyncio.run(main())
Mastercard
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Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Mastercard MCP Server

Connect Mastercard payment infrastructure to any AI agent and unlock powerful payment intelligence, fraud detection, merchant discovery, and card validation capabilities through natural conversation.

LlamaIndex agents combine Mastercard tool responses with indexed documents for comprehensive, grounded answers. Connect 12 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.

What you can do

  • BIN Lookup — Identify any payment card's issuer bank, card type (credit/debit/prepaid/commercial), category (Standard/Gold/Platinum/World/World Elite), issuing country, and special flags from just the first 6-8 digits
  • Account Validation — Verify if a payment card number is active and valid before processing transactions, reducing declined payments and fraud risk
  • Merchant Search — Find Mastercard-accepting merchants near any GPS coordinates, filterable by business category (MCC codes)
  • Places Discovery — Discover nearby payment-accepting locations with digital wallet support (Apple Pay, Google Pay, contactless)
  • Address-Based Search — Search for merchants by street address instead of coordinates for user-friendly location queries
  • Merchant Details — Retrieve complete information about specific merchants including addresses, MCC codes, and accepted payment methods
  • MCC Code Reference — Access the complete Merchant Category Code database to understand business classifications
  • Fraud Reporting — Submit confirmed fraudulent transactions to Mastercard's Fraud and Loss Database to protect the network
  • Nearby Locations — Discover ATMs, merchants, and points of interest around any geographic location

The Mastercard MCP Server exposes 12 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Mastercard to LlamaIndex via MCP

Follow these steps to integrate the Mastercard MCP Server with LlamaIndex.

01

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

03

Run the agent

Save to agent.py and run: python agent.py

04

Explore tools

The agent discovers 12 tools from Mastercard

Why Use LlamaIndex with the Mastercard MCP Server

LlamaIndex provides unique advantages when paired with Mastercard through the Model Context Protocol.

01

Data-first architecture: LlamaIndex agents combine Mastercard tool responses with indexed documents for comprehensive, grounded answers

02

Query pipeline framework lets you chain Mastercard tool calls with transformations, filters, and re-rankers in a typed pipeline

03

Multi-source reasoning: agents can query Mastercard, a vector store, and a SQL database in a single turn and synthesize results

04

Observability integrations show exactly what Mastercard tools were called, what data was returned, and how it influenced the final answer

Mastercard + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the Mastercard MCP Server delivers measurable value.

01

Hybrid search: combine Mastercard real-time data with embedded document indexes for answers that are both current and comprehensive

02

Data enrichment: query Mastercard to augment indexed data with live information before generating user-facing responses

03

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Mastercard for fresh data

04

Analytical workflows: chain Mastercard queries with LlamaIndex's data connectors to build multi-source analytical reports

Mastercard MCP Tools for LlamaIndex (12)

These 12 tools become available when you connect Mastercard to LlamaIndex via MCP:

01

bin_lookup

Returns comprehensive card information including: issuer bank name, card type (credit/debit/prepaid/commercial), card category (Standard/Gold/Platinum/World/World Elite), issuing country, currency, and special flags (healthcare, payroll, purchasing). Use this to identify unknown cards, validate card ranges before transactions, determine cross-border fees, or understand the cardholder profile. The accountNumberPrefix parameter must be 6-8 numeric digits. Optional parameters (currencyCode, paymentType, merchantCategoryCode) provide more precise results for specific transaction contexts. Identify card issuer, type, and details from the first 6-8 digits of a payment card number

02

bin_lookup_post

Returns identical card identification data: issuer bank, card type, category, country, and product flags. Use this method when handling sensitive payment data in compliance-focused applications. The accountNumberPrefix should be 6-8 digits. Optional context parameters (currency, payment type, MCC) refine results. Identify card issuer using POST method for enhanced security with sensitive card data

03

get_merchant

Returns full address, contact information, MCC code, operating hours, and accepted payment methods. Use this to get in-depth information about a specific merchant location after finding it via search. The merchant ID is a unique identifier returned by the search_merchants tool. Get detailed information about a specific Mastercard-accepting merchant

04

get_place_details

Returns full address, coordinates, MCC code, payment methods accepted, operating hours, and other merchant attributes. Use this after a places search to drill down into a specific location. The locationId is returned by search_places or search_places_by_address tools. Get complete details for a specific merchant place by its location ID

05

merchant_category_codes

MCC codes are 4-digit numbers that classify businesses by type (e.g., 5411 = Grocery Stores, 5812 = Restaurants, 4511 = Airlines). Use this to understand merchant classifications, filter searches by business type, or decode MCC values found in transaction data. Optional limit parameter controls how many codes to return. List all Merchant Category Codes (MCC) used to classify business types

06

merchant_industry_codes

Industry codes group related MCC codes into higher-level categories. Use this to understand the hierarchical classification of merchants, analyze industry-level spending patterns, or build category navigation interfaces. List all merchant industry codes for broader business classification

07

nearby_locations

Returns names, addresses, categories, and distances from the search point. Use this for "what is nearby" queries, travel planning, or finding payment infrastructure in an area. Latitude and longitude are required. Radius in meters defines the search area. Limit controls maximum results returned. Discover points of interest and payment locations near GPS coordinates

08

search_merchants

Returns merchant names, addresses, MCC codes, and precise coordinates. Use this to find nearby payment-accepting locations, analyze merchant density in an area, or build "find merchants near me" features. Latitude and longitude are required as strings (e.g., "-23.5505", "-46.6333"). Radius is in meters (e.g., 5000 for 5km). Optionally filter by MCC category code (e.g., "5411" for grocery stores, "5812" for restaurants). Limit controls result count (max 50). Find Mastercard-accepting merchants near specific GPS coordinates filtered by category

09

search_places

Returns detailed merchant information including whether they accept Apple Pay, Google Pay, contactless payments, and their MCC classification. Use this when users need to find payment-accepting locations with specific digital wallet support. Latitude and longitude are required as numbers. Distance is in kilometers. Optionally filter by country code (ISO 3166-1 alpha-2) and payment capabilities (hasApplePay, hasGooglePay). Search for merchant places using GPS coordinates with payment method filters

10

search_places_by_address

The API geocodes the address internally. Returns nearby merchants with payment capability details (Apple Pay, Google Pay, contactless). Use this when users provide an address rather than GPS coordinates. Required: address line 1, city, country code, and postal code. Optional: state/province code (countrySubdivisionCode) for more precise results. Example: addressLine1="1600 Amphitheatre Pkwy", city="Mountain View", countryCode="US", postalCode="94043". Search for merchant places using a street address instead of coordinates

11

submit_fraud_report

This is a critical tool for issuers and processors to flag fraudulent transactions in real-time. Required fields: accountNumber (card number), transactionAmount, transactionCurrency (ISO 4217), and fraudTypeCode. Fraud type codes: "01" = Stolen Card Fraud, "02" = Never Received Card, "03" = Fraudulent Application, "04" = Counterfeit Card Fraud. Optional: fraudAmount (if different from transaction amount), transactionDate (YYYY-MM-DD). Use this only for confirmed fraud cases — never for suspected or disputed transactions. This helps Mastercard improve fraud detection and reduce false positives across the network. IMPORTANT: This action should only be performed by authorized fraud management personnel. Report a confirmed fraudulent transaction to Mastercard Fraud and Loss Database

12

validate_account

Returns validation status (VALID/INVALID), account type, and issuer information. Use this to verify card validity before processing transactions, reduce declined transactions, or perform account verification during onboarding. Required: accountNumber (full card number). Optional: expiryDate (MMYY format), cardholderName for enhanced validation. Handle card numbers securely — never log or store full PANs. Validate a payment card account number to check if it is active and valid

Example Prompts for Mastercard in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with Mastercard immediately.

01

"What type of card is 542418 and which bank issued it?"

02

"Find restaurants near São Paulo city center that accept Mastercard within 3km."

03

"Validate card number 5123456789012346 before I process this payment."

Troubleshooting Mastercard MCP Server with LlamaIndex

Common issues when connecting Mastercard to LlamaIndex through the Vinkius, and how to resolve them.

01

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Mastercard + LlamaIndex FAQ

Common questions about integrating Mastercard MCP Server with LlamaIndex.

01

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.
02

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query Mastercard tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.
03

Does LlamaIndex support async MCP calls?

Yes. LlamaIndex's async agent framework supports concurrent MCP tool calls for high-throughput data processing pipelines.

Connect Mastercard to LlamaIndex

Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.