Rabobank Training Demo

A minimal, realistic training project for a 1-hour MCP session with developers.

The project demonstrates how GitHub Copilot in Visual Studio Code can use an internal MCP server to safely access approved internal APIs, documentation and review prompts.

All data is fictional. No real Rabobank data is included.

---

What this demo contains

rabobank_internal_mcp_uv_demo/
├─ app/
│  ├─ data.py              # Fake internal banking data
│  ├─ internal_api.py      # Internal FastAPI API
│  ├─ mcp_server.py        # MCP server wrapping the internal API
│  ├─ run_api.py           # uv script entrypoint for the API
│  └─ __init__.py
├─ .vscode/
│  ├─ mcp.json             # VS Code MCP config using uv
│  └─ tasks.json           # Optional VS Code tasks
├─ scripts/
│  ├─ demo-calls.ps1       # PowerShell API test calls
│  └─ demo-calls.sh        # Bash API test calls
├─ .env.example
├─ .python-version
├─ pyproject.toml
└─ README.md

---

Learning goal

Developers learn that an MCP server can act as a controlled AI-facing layer over internal systems.

GitHub Copilot in VS Code
          │
          ▼
      MCP Client
          │
          ▼
 Internal MCP Server
          │
 ┌────────┼────────┬─────────────┐
 ▼        ▼        ▼             ▼
Internal  API      Policies      Architecture
API       Catalog  / Standards   Checks

---

Prerequisite: uv

Check if uv is available:

uv --version

Install uv on Windows:

winget install astral-sh.uv

Alternative Windows install:

powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

macOS/Linux:

curl -LsSf https://astral.sh/uv/install.sh | sh

---

Setup

From the project folder:

uv sync

This creates the virtual environment and installs dependencies from pyproject.toml.

---

Training Pages

This repository also contains HTML training material:

• index.html - self-study guide for MCP and Rabobank Design System context
• mcp-extension-lab.html - hands-on developer lab for extending this MCP server
• mcp-extension-trainer-answer-key.html - trainer guide with expected solution and demo flow

---

Step 1 — Run the internal API

Terminal 1:

uv run bank-api

Open the FastAPI docs:

http://127.0.0.1:8000/docs

Test the health endpoint:

curl http://127.0.0.1:8000/health

Most endpoints require the demo API key:

curl -H "x-api-key: training-demo-key" http://127.0.0.1:8000/customers/CUST-1001

PowerShell alternative:

$Headers = @{ "x-api-key" = "training-demo-key" }
Invoke-RestMethod -Uri "http://127.0.0.1:8000/customers/CUST-1001" -Headers $Headers

---

Step 2 — Run the MCP server

Normally VS Code starts the MCP server using .vscode/mcp.json.

For a manual smoke test, open Terminal 2:

uv run bank-mcp

The MCP server uses stdio transport, so it may look like it is waiting. That is expected.

---

Step 3 — Connect in Visual Studio Code

The example config is in:

.vscode/mcp.json

It starts the MCP server with:

uv run bank-mcp

Important: keep the internal API running in Terminal 1.

---

MCP tools

get_customer_profile(customer_id)

Example IDs:

• CUST-1001
• CUST-2002

Example prompt:

Use the internal MCP server to retrieve customer CUST-1001 and summarize the active products.

get_product_info(product_id)

Example IDs:

• MORTGAGE-FLEX
• PAYMENT-PLUS
• BUSINESS-ACCOUNT

Example prompt:

Use the internal MCP server to explain product MORTGAGE-FLEX for a developer who needs to call the product API.

get_api_endpoint_info(api_name)

Example API names:

• customer-onboarding
• product-catalog

Example prompt:

Use the internal MCP server to inspect the customer-onboarding API and tell me which endpoint creates a new onboarding case.

run_architecture_check(service_name)

Example prompt:

Run an architecture check for CustomerOnboardingService and summarize the findings as action items.

---

MCP resources

policy://api-security

Example prompt:

Use the policy://api-security resource and summarize the security requirements for internal APIs.

architecture://event-driven-standards

Example prompt:

Use the architecture://event-driven-standards resource and explain what every event must contain.

---

MCP prompt

api_security_review_prompt(api_name, endpoint)

Example prompt:

Use the api_security_review_prompt for the customer-onboarding API and endpoint /onboarding/cases.

---

Trainer flow for 1 hour

0–10 min — Explain MCP

MCP is a standard way to let AI clients use tools, resources and prompts from approved systems.

10–20 min — Show the internal API

Open:

http://127.0.0.1:8000/docs

Show that it represents internal systems:

• Customer API
• Product API
• API catalog
• Policies
• Architecture check

20–35 min — Show the MCP server

Open app/mcp_server.py and explain:

• Tools perform actions or retrieve specific data
• Resources expose readable knowledge
• Prompts standardize repeatable tasks

35–50 min — Use GitHub Copilot in VS Code

Run the demo prompts from this README.

50–60 min — Extension exercise

Ask participants to add one new tool:

@mcp.tool
def list_customer_products(customer_id: str) -> list[str]:
    customer = internal_get(f"/customers/{customer_id}")
    return customer["active_products"]

Then ask Copilot:

Use the internal MCP server to list the active products for customer CUST-1001.

---

Security discussion points

This demo intentionally uses fake data. In a real organization, discuss:

• Internal allowlist for MCP servers
• Authentication and authorization
• Least privilege
• Audit logging
• Correlation IDs
• Output filtering
• No direct production database access
• API gateway usage
• Data classification
• Separate dev/test/prod environments

---

Troubleshooting

uv is not recognized

Restart the terminal after installing uv.

API endpoint returns 401

Add the demo API key header:

x-api-key: training-demo-key

MCP server seems stuck

That is normal for stdio MCP servers. It waits for the MCP client.

Port 8000 already in use

Change the port in app/run_api.py or stop the other process.