AIVA Credit Card MCP Server & FastAPI Gateway

A decoupled, stateful Model Context Protocol (MCP) server and HTTP REST Gateway styled exactly as a NextGen Bank Credit Card IVR Integration. It bridges the gap between raw backend core banking mainframes and conversational voice AI frameworks (such as Twilio Voice, Whisper, ElevenLabs, and CrewAI).

🧠 Core Philosophy: Dual-Channel Response Design

In conversational banking, there is a fundamental conflict between banking mainframes and customer experience:

1. Core Banking Mainframes: Require detailed system audit logs ([SYSTEM_LOG]) for auditing, fraud tracking, and transactional ledgers.

2. Customers (Voice dialogue): Cannot understand technical backend system logs. Speaking these will ruin the conversational flow.

AIVA resolves this by implementing a Dual-Channel Response Architecture:

• 🗣️ Customer Dialogue ([AIVA IVR Dialogue]): Friendly, empathetic, and 100% natural conversational language to be spoken directly to the user (via text-to-speech). All technical jargon is completely removed.

• ⚙️ System Audit Log ([SYSTEM_LOG]): Separated backend log structure appended at the bottom, housing the precise status details for downstream databases and engineering audits.

Related MCP server: mcp-apps-demo-engine

🔒 Implemented Core Banking & Security Safeguards

We have designed and verified five industry-grade banking workflow and security guards in the database core logic:

1. Compromised Card Safety (Stolen/Hot-Carded)

   • Rule: Once a card is marked stolen/compromised via confirmed fraud (confirm_fraud), self-service unblocking is permanently disabled. Any unblock attempt (even with correct security answers) is rejected, and the customer is routed directly to a human representative.

2. Duplicate Dispute Prevention (Already Disputed)

   • Rule: Blocks subsequent dispute submissions on the same transaction ID to prevent double-crediting inflation and audit duplicates.

3. Override Blocks on Restricted Card (Blocked/Stolen Card Hold)

   • Rule: Rejects credit limit increase requests on cards that are Blocked, Locked Out, or Stolen.

4. Fraud Clearing Validation (Transaction Not Flagged)

   • Rule: Prevents clearing fraud alerts (deny_fraud) on normal successful transactions that were never flagged as suspicious by our fraud models.

5. 3-Strike KBA Verification Lockout (Verification Attempts Exceeded)

   • Rule: To prevent brute-forcing cardholder verification, self-service unblocking locks out after exactly 3 failed attempts, requiring human agent verification.

📊 Isolated Demo Schema (3 Profiles)

To deliver a non-contaminating, scalable and bulletproof live demonstration, the database seeds three distinct customer accounts formatted identically to real NextGen Bank Account Numbers (10 digits). Each profile isolates exactly one business flow:

graph TD
    A[MongoDB Database] --> B(nextgen-creditcards-ivr Collection)
    
    B --> C[Account 1: Failed Transaction]
    C --> C1[Vedant]
    C --> C2[Account No: 770321003]
    C --> C3[Card ending in 7003]
    C --> C4[Flow: Limit decline -> temporary limit increase to $2,000]
    
    B --> D[Account 2: Card Blocked]
    D --> D1[Maria Gonzalez]
    D --> D2[Account No: +15550102]
    D --> D3[Card ending in 8121]
    D --> D4[Flow: KBA question 'Buddy' -> unblock to Active / 3-Strike Lockout]
    
    B --> E[Account 3: Fraud Suspicion]
    E --> E1[Emily Watson]
    E --> E2[Account No: +15550104]
    E --> E3[Card ending in 5528]
    E --> E4[Flow: Confirm Fraud -> disputes txn, permanent hot-card block, Apple Pay digital wallet copy]

🛠️ Setup & Configuration

1. Prerequisites

• Python: 3.10+

• MongoDB: A running MongoDB instance (Local or MongoDB Atlas)

2. Environment Configuration

Create a .env file in the root directory to manage your configurations:

MONGO_URI=mongodb+srv://<username>:<password>@<cluster>.mongodb.net/?retryWrites=true&w=majority
MONGO_DB_NAME=wf-ivr
MONGO_COLLECTION_NAME=creditcards
SERVER_HOST=0.0.0.0
SERVER_PORT=8000

3. Installation

Install core requirements using pip:

pip install -r requirements.txt

🚀 Execution & Verification

1. Seeding and Auto-testing

Run the programmatic automation suite to completely reset the database, execute all 18 standard and negative test cases, and dynamically compile the beautiful visual HTML documentation:

python run_automated_tests.py

This test runner executes:

• Vedant limit increase happy path & restricted card limit override block.

• Maria Gonzalez unblocking happy path & sequential 3-strike brute-force lockout.

• Emily Watson fraud disputes, duplicate disputes block, and unblocking compromised card blocks.

• Emily Watson fraud denial clearing & non-flagged fraud clearing block.

2. Start HTTP Gateway (Postman Testing)

Start the FastAPI REST gateway to test using Postman or manual HTTP POST payloads:

python server.py

• Endpoint: POST http://localhost:8000/api/credit-card

• Swagger UI Docs: http://localhost:8000/docs

• HTML Report: Open integration_docs.html in a web browser to review the visual conversation chat timeline, high-resolution visual sequence diagrams, and copy-paste actual live JSON requests/responses.

3. Start Stdio MCP Mode (CrewAI Integration)

To bind the Model Context Protocol directly to the CrewAI agent orchestrator via stdio:

python server.py --mcp

CrewAI MCP Configuration (mcp_config.json)

Configure your CrewAI orchestrator or desktop client using this block:

{
  "mcpServers": {
    "aiva-creditcard-mcp": {
      "command": "python",
      "args": ["C:/Users/bhatn/OneDrive/Documents/Projects/AntiGravity/aiva-creditcard-mcp/server.py", "--mcp"]
    }
  }
}

📂 Project Architecture

• server.py: Houses the dual FastMCP stdio server and FastAPI REST gateway.

• run_automated_tests.py: Executes the 18 automated test suites, capturing live JSON traces to compile the master documentation.

• seed_db.py: Seeds MongoDB with NextGen Bank test profiles.

• integration_docs.html: Handover reference with pixel-clean fullscreen sequence diagram modals, conversational chats, and live REST JSON traces.

• .gitignore: Excludes credentials (.env) and python compilation directories from Git tracking.