MCP Demo — GitHub Copilot + Your Database

What if you could ask Copilot a question and it queried your database to answer it? That's what this demo shows. Clone it, run two commands, and watch it work.

What is MCP?

Model Context Protocol (MCP) is an open standard that lets AI assistants like GitHub Copilot connect directly to your tools and data — in real time, with guardrails you control.

Instead of copy-pasting data into chat, Copilot just asks your server:

MCP isn't AI-only. The same server can be called by scripts, pipelines, or any client. The LLM is just the first killer app.

See It In Action

Real responses from this running server:

"Show me all products under $200"

Guardrail in action — PII is auto-redacted:

{
  "rows": [{"id": 1, "name": "Alice Johnson", "email": "[REDACTED]", "role": "admin"}],
  "pii_notice": "The following field(s) were redacted to protect PII: email"
}

Dangerous query? Blocked before it touches the database:

{ "success": false, "error": "Query contains a blocked pattern and was rejected for security reasons." }

Get Running in 3 Steps

Prerequisites: Python 3.12+, VS Code, GitHub Copilot extension

# 1. Install
git clone https://github.com/coderkanasu/mcp-demo && cd mcp-demo
pip install -r requirements.txt   # simple install
# or: pip install -e .            # editable install (for development)

# 2. Set up the database
python mcp_server/db/init_db.py

# 3. Verify it works
python mcp_server/tools/sql_query_tool.py

Connect to Copilot: A .vscode/mcp.json is already included — open this repo in VS Code and Copilot Agent mode picks it up automatically. No manual config needed.

{
  "servers": {
    "demo-sql-server": {
      "type": "stdio",
      "command": "python3",
      "args": ["-m", "mcp_server.server"],
      "env": { "PYTHONPATH": "${workspaceFolder}" }
    }
  }
}

Then open Copilot Chat → Agent mode and start asking questions.

Built-in Guardrails

This is a demo — but it ships with real security controls, not placeholders:

Not included (needed for production): user authentication, role-based access control, write-operation approval gates. See PRODUCTION_READINESS.md.

What's Inside

mcp_server/
├── server.py               # MCP server — rate limiting, routing, error handling
├── tools/
│   └── sql_query_tool.py   # PII scrubbing, injection blocking, query execution
└── db/
    ├── init_db.py          # Seeds sample e-commerce data
    └── demo.db             # SQLite database (users, products, orders)
.vscode/
└── mcp.json                # Plug-and-play Copilot config
requirements.txt            # pip install -r requirements.txt
pyproject.toml              # package metadata + dev dependencies

How It Works

You (Copilot Chat)
      │  "Show me all products under $200"
      ▼
GitHub Copilot (Agent mode)
      │  calls get_schema, then execute_query
      ▼
MCP Server  ←── validates, rate-limits, scrubs PII
      │
      ▼
SQLite Database  ←── returns rows
      │
      ▼
Copilot formats and presents the answer

Want to extend it?

• Add a new tool: create a class in mcp_server/tools/, register it in server.py
• Use a real database: swap SQLite for PostgreSQL/MySQL in sql_query_tool.py
• Add auth: wrap execute_query with a token check

Requirements

• Python 3.12+
• VS Code with GitHub Copilot (Agent mode)
• macOS / Linux / Windows

License

MIT — free to use, fork, and adapt.