Which integrations are available for this server?

Allows the MCP server to be used as an interface for querying MySQL databases, providing tools for AI agents to retrieve data and inspect database schemas. Allows the MCP server to be used as an interface for querying PostgreSQL databases, providing tools for AI agents to retrieve data and inspect database schemas. Enables querying of SQLite databases to retrieve schema information and execute SQL queries, featuring built-in security guardrails like PII redaction and SQL injection blocking.

How do I use MCP Demo — GitHub Copilot + Your Database?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@MCP Demo — GitHub Copilot + Your Database Show me the top 5 most expensive products in stock" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

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:

You type in Copilot Chat	What happens
`What tables are in the database?`	Copilot calls `get_schema`, returns your full schema
`Show me all products under $200`	Copilot writes and runs the SQL query live
`Which users have the admin role?`	Instant answer — emails auto-redacted

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"

Product	Price	Stock
Wireless Mouse	$49.99	120
USB-C Hub	$79.99	60
External SSD (1TB)	$129.99	35
Mechanical Keyboard	$149.99	45
Webcam (4K)	$199.99	12

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:

Guardrail	Detail
PII auto-redaction	`email`, `phone`, `address`, `password`, and 9 other field patterns scrubbed from all results
SQL injection blocking	17 patterns blocked: `UNION SELECT`, `OR 1=1`, stacked queries, `DROP`, `--` comments, and more
Allowed operations only	`SELECT`, `INSERT`, `UPDATE` only — `DROP`, `DELETE`, `TRUNCATE` rejected
Row cap	100 rows max per query — prevents bulk extraction
Rate limiting	30 calls per 60-second window
Audit logging	Every query logged with timestamp and outcome
Sanitised errors	Stack traces never returned to the LLM

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