Local Data Engineering MCP
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
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.pyregisters five read-only tools with the official Python MCP SDK.src/data_service.pycreates and queries the local SQLite demo database.src/models.pydefines the tools' structured outputs;tests/covers the service and MCP interface.
Related MCP server: MCP SQLite Server (Read-Only)
Available MCP tools
get_table_schema(table_name)get_table_row_count(table_name)get_table_freshness(table_name)run_readonly_query(query)— accepts oneSELECTand returns at most 100 rowsget_pipeline_status(pipeline_name)
Installation
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txtHow to run it
Start the stdio server:
mcp run src/server.pyFor 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.Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
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Maintenance
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