Lakexpress Mcp
Automate database-to-cloud Parquet lake loads through your agent via LakeXpress without stitching export and upload steps manually.
Overview
LakeXpress MCP is an Operate-phase MCP server that runs automated database-to-cloud Parquet data pipelines through LakeXpress.
What is this MCP server?
- LakeXpress MCP: automated database-to-cloud pipeline output as Parquet
- PyPI lakexpress-mcp 0.1.6 with stdio transport
- LONGER default timeout LAKEXPRESS_TIMEOUT 3600 seconds for pipeline runs
- FASTBCP_DIR_PATH auto-fills fastbcp_dir_path when FastBCP is co-installed
- Preview-only without LAKEXPRESS_PATH binary
- Server version 0.1.6 on PyPI identifier lakexpress-mcp
- Default LAKEXPRESS_TIMEOUT 3600 seconds
- Five documented environment variables including FASTBCP_DIR_PATH
What problem does it solve?
Building a reliable DB-to-lake Parquet path by hand means brittle glue between export, format conversion, and cloud upload.
Who is it for?
Indie products that want a simple operational lake feed from SQL databases without a full Spark estate.
Skip if: Teams that only need in-database analytics or real-time streaming ingestion without batch Parquet lands.
What do I get? / Deliverables
Your agent can launch governed LakeXpress jobs that land Parquet datasets in cloud storage with extended timeouts and structured logs.
- Parquet datasets in configured cloud destinations
- Pipeline execution logs under LAKEXPRESS_LOG_DIR
- Agent-scheduled lake loads with 3600s default timeout window
Recommended MCP Servers
Journey fit
Lake-style analytics pipelines are operated infra: you already ship the app and now need durable cloud datasets for BI and ML. Infra subphase fits automated Parquet pipelines that land warehouse-ready files in object storage from operational databases.
How it compares
End-to-end Parquet lake MCP pipeline, not a raw file-only FastBCP export.
Common Questions / FAQ
Who is lakexpress-mcp for?
Builders operating production databases who want MCP-driven Parquet datasets in cloud storage for analytics.
When should I use lakexpress-mcp?
Use it when you need recurring or large batch loads from a database into a cloud data lake as Parquet during operate/infra work.
How do I add lakexpress-mcp to my agent?
Install lakexpress-mcp from PyPI, configure stdio MCP in your agent, set LAKEXPRESS_PATH and optional FASTBCP_DIR_PATH, then set timeout and log environment variables.