secure-banking-mcp

secure-banking-mcp

Demonstrates secure banking operations with mock data, enabling an AI assistant to query accounts while identity and authorization are enforced via signed tokens outside the conversation.

Category
Visit Server

README

Secure Banking MCP

This is a working demonstration of an AI assistant accessing mock banking data without being trusted to decide who the user is.

The assistant may ask for an account by its account number. It cannot supply a user, company, role, or tenant. Those facts come from a signed access token carried outside the conversation. Every database lookup combines the requested account with that verified identity.

This project contains fictional data and development tokens. It is an educational reference, not a deployable bank.

Quickstart

Requirements: Python 3.12+ and uv.

uv sync --extra dev
uv run secure-banking-mcp

The MCP endpoint is http://127.0.0.1:8000/mcp. In VS Code, start the server and connect using the included .vscode/mcp.json. Enter demo-alice-token when prompted.

Run the security evidence suite:

uv run pytest

This produces both raw Allure evidence in allure-results/ and a self-contained HTML report at allure-report/index.html. Open the HTML file directly in a browser; no Allure CLI, Java installation, or report server is required.

The HTML is a portable pytest report rather than the official Allure dashboard. The raw evidence remains compatible with the official Allure CLI if that richer dashboard is needed later.

What Protects The Data

Think of the language model as an untrusted person filling in a request form. It can choose an account number and an amount, but it cannot fill in the "who am I?" field because that field does not exist on the form.

  1. The MCP client sends a bearer token outside the prompt and tool arguments.
  2. FastMCP verifies the token signature, issuer, audience, and expiry in production mode.
  3. A dependency converts verified claims into an internal Principal.
  4. A scope check decides whether that person may use the requested capability.
  5. SQLite queries require the account, tenant, and owner to match together.
  6. Failure messages do not reveal whether another customer's account exists.
flowchart LR
    U[Person] --> C[MCP client]
    L[Untrusted model] -->|account and amount only| C
    C -->|tool arguments| M[FastMCP]
    C -->|bearer token, outside prompt| V[Token verifier]
    V --> P[Trusted principal]
    M --> A[Scope guard]
    P --> A
    A --> S[Banking service]
    S -->|account + verified tenant + verified owner| D[(SQLite mock data)]

Demonstrated Attacks

The tests prove that:

  • Prompt instructions cannot change the authenticated identity.
  • Replacing Alice's account number with Mallory's returns a generic denial.
  • Adding user_id, tenant_id, or role to tool input is rejected by the schema.
  • Read-only users cannot call money-moving services.
  • A transfer cannot cross an ownership or tenant boundary.

Production Boundary

Set all three variables to replace the local static-token verifier with asymmetric JWT verification:

export BANKING_JWKS_URI=https://identity.example/.well-known/jwks.json
export BANKING_JWT_ISSUER=https://identity.example/
export BANKING_JWT_AUDIENCE=secure-banking-mcp

Production should also use TLS, a managed database with row-level security, short-lived tokens, key rotation, immutable audit logs, rate limits, and a policy engine for richer rules. Never enable shared response caching for identity-derived financial results.

See docs/architecture.md for the component decisions and trust boundaries.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured