MCP Live Showcase
Provides tools to list tables, describe schemas, and run SELECT queries on a SQLite database.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCP Live ShowcaseCheck if aspirin is safe for patient P-001"
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 Live Showcase
Two tiny, self-contained MCP servers for a live workshop demo, plus a seeded database. Built on the official MCP Python SDK (FastMCP).
Demo data only. The clinical server uses fake patients and a fake interaction table. It is not for clinical use.
What's here
File | What it is |
| An MCP server with |
| A "talk to your data" MCP server over |
| Creates/reseeds |
| Pre-seeded SQLite (12 rows of regional sales). |
Related MCP server: horizon-mcp-demo-extended-v2
Setup
python -m venv .venv && source .venv/bin/activate # optional
pip install -r requirements.txt
python seed_db.py # creates sales.db (already included, re-run to reset)Test each server in the MCP Inspector (no AI needed)
mcp dev clinical_tools.py # opens the Inspector in your browser
mcp dev data_explorer.pyConnect, open the Tools tab, run a tool, see the JSON. Great for proving the server works before any agent touches it.
Register the servers with your host
Claude Code (stdio — use absolute paths):
claude mcp add clinical-tools -- python /ABS/PATH/clinical_tools.py
claude mcp add data-explorer -- python /ABS/PATH/data_explorer.py
/mcp # inside Claude Code: confirm both show "connected"Claude Desktop:
mcp install clinical_tools.py --name "Clinical Tools"
mcp install data_explorer.py --name "Data Explorer"Demo prompts (the showcase sequence)
Talk to your data —
Which region had the highest total sales in Q2? Show the totals per region.Clinical lookup —
Look up patient P-001 and show their latest labs, flagging anything abnormal.Decision support —
For patient P-001, is it safe to prescribe aspirin?→ flags the warfarin interaction.Reusable prompt — run the
/triageprompt withP-001.The finale (multi-server + GitHub):
For patient P-001, check whether aspirin is safe. If there's a conflict, open a GitHub issue in <owner>/<repo> titled "Prescribing alert: P-001" describing it.→ the agent uses clinical-tools and the GitHub server in one flow.
Publish this project to a GitHub repo (hand to Claude Code)
Open this folder in Claude Code and paste:
Initialise a git repository in this folder, then create a new PUBLIC GitHub repository
called "mcp-showcase" under my account using the connected GitHub MCP server (fall back
to the gh CLI or git if needed). Commit every file with the message "MCP showcase: two
custom servers + seeded data", push to the main branch, and reply with the repo URL.That's it — "deploy" here means publishing the source to GitHub; the servers themselves run locally over stdio for the demo.
This server cannot be deployed
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