Local Data Engineering MCP

A minimal MCP server that lets an AI agent inspect a mock data platform without cloud credentials. It uses SQLite data for customers, orders, products, and local pipeline status.

Architecture

• src/server.py registers five read-only tools with the official Python MCP SDK.

• src/data_service.py creates and queries the local SQLite demo database.

• src/models.py defines the tools' structured outputs; tests/ covers the service and MCP interface.

Related MCP server: Context Catalog MCP

Available MCP tools

• get_table_schema(table_name)

• get_table_row_count(table_name)

• get_table_freshness(table_name)

• run_readonly_query(query) — accepts one SELECT and returns at most 100 rows

• get_pipeline_status(pipeline_name)

Installation

python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

How to run it

Start the stdio server:

mcp run src/server.py

For interactive development, run mcp dev src/server.py to open MCP Inspector.

Example interaction

User: Why is the orders table stale?

Agent:
1. get_table_freshness("orders") -> status: stale, age_hours: 71.0
2. get_pipeline_status("orders_pipeline") -> status: failed
3. get_table_schema("orders") -> order_id, customer_id, product_id,
   quantity, ordered_at, updated_at

Conclusion: the orders pipeline timed out, so no new orders were loaded.