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Standardize, reshape, and normalize messy data — CSV, Excel, Parquet, S3, databases.
About
Standardize, reshape, and normalize messy data — CSV, Excel, Parquet, S3, databases.
Remote endpoints: streamable-http: https://goldenflow-mcp-production.up.railway.app/mcp/
Security Report
9.0
Low Risk9.0Low RiskValid MCP server (2 strong, 1 medium validity signals). 2 known CVEs in dependencies (0 critical, 1 high severity) Package registry verified. Imported from the Official MCP Registry. Trust signals: trusted author (5/5 approved); 3 highly-trusted packages.
7 files analyzed · 3 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Required
This plugin requests these system permissions. Most are normal for its category.
How to Install & Connect
Available as Local & Remote
This plugin can run on your machine or connect to a hosted endpoint. during install.
Getting Started
Once installed, try these example prompts and explore these capabilities:
- 1"Clean up and standardize my customer data"
- 2"What transforms would fix the issues GoldenCheck found?"
- 3"Show me the diff between the original and cleaned file"
- 4"Learn a transform config from my sales data patterns"
- 5Tool: transform — Transform a data file with zero-config or config-driven rules
- 6Tool: map — Auto-map schemas between source and target files
- 7Tool: profile — Profile a data file showing column types, nulls, and patterns
- 8Tool: learn — Generate a YAML config from detected data patterns
- 9Tool: diff — Compare two data files and show what changed
- 10Tool: validate — Dry-run a transform to preview changes without writing output
- 11Tool: select_from_findings — Map GoldenCheck findings to recommended transforms
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