GoldenFlow

benseverndev-oss/goldenflow

GoldenFlow handles the data cleaning work that usually lives in throwaway scripts: normalizing phone numbers to E.164, standardizing dates to ISO 8601, fixing inconsistent column names across systems, stripping whitespace and unicode artifacts. The MCP server exposes transform, profile, map, and validate operations, so Claude can clean CSVs, Excel files, Parquet, or live database tables without you writing transformation configs. Zero-config mode auto-detects what needs fixing and generates an audit manifest showing every change. Reach for this when you're building pipelines that ingest messy data from external sources or need to reconcile schemas between systems. Also available as Python and TypeScript packages if you want to run transforms programmatically outside the MCP layer.

GitHub stars: 1
tools: 10
transport: STDIO, HTTP
last updated: Aug 16, 2026

View on GitHub

Install

From registry metadata

$ npx add-mcp https://goldenflow-mcp-production.up.railway.app/mcp/ --name goldenflow

Run in your terminal. add-mcp asks which agents to add it to (Claude Code, Codex, Cursor and more). Add -g to install it for every project.

Review the command, arguments and environment values before installing. MCP servers run with your local permissions.

Other ways

Claude Code

$ claude mcp add --transport http goldenflow https://goldenflow-mcp-production.up.railway.app/mcp/

Run in your terminal. Add --scope user to make it available in every project.

Tools

Verified live · 10 tools

Verified live against the running server on Jun 10, 2026.

transformTransform a data file using GoldenFlow. Zero-config or config-driven.2 params

Transform a data file using GoldenFlow. Zero-config or config-driven.

Parameters* required

configstring

Optional YAML config path

path*string

Path to data file

mapAuto-map schemas between source and target files.2 params

Auto-map schemas between source and target files.

Parameters* required

source*string

Source file path

target*string

Target file path

profileProfile a data file showing column types, nulls, and patterns.1 params

Profile a data file showing column types, nulls, and patterns.

Parameters* required

path*string

Path to data file

learnGenerate a YAML config from data patterns.1 params

Generate a YAML config from data patterns.

Parameters* required

path*string

Path to data file

diffCompare two data files and show what changed (added, removed, modified rows).2 params

Compare two data files and show what changed (added, removed, modified rows).

Parameters* required

path_after*string

Path to transformed file

path_before*string

Path to original file

validateDry-run transform on a file. Shows what would change without writing output.2 params

Dry-run transform on a file. Shows what would change without writing output.

Parameters* required

configstring

Optional YAML config path

path*string

Path to data file

list_transformsList all registered transforms with their modes, input types, and auto-apply status.

List all registered transforms with their modes, input types, and auto-apply status.

No parameters. Call it with no arguments.

explain_transformDescribe what a specific transform does, its mode, and input types.1 params

Describe what a specific transform does, its mode, and input types.

Parameters* required

transform_name*string

Name of the transform

list_domainsList available domain packs (e.g., people_hr, ecommerce, finance).

List available domain packs (e.g., people_hr, ecommerce, finance).

No parameters. Call it with no arguments.

select_from_findingsMap GoldenCheck findings to recommended GoldenFlow transforms. Bridge tool for Check-to-Flow handoff.1 params

Map GoldenCheck findings to recommended GoldenFlow transforms. Bridge tool for Check-to-Flow handoff.

Parameters* required

findings*array

List of GoldenCheck findings (each with 'check' and 'column' fields)

Readme

Moved. This repo has moved into the benzsevern/goldenmatch monorepo at packages/python/goldenflow (and packages/typescript/goldenflow)/. This repo is archived; new development happens in the monorepo.

GoldenFlow

Data transformation toolkit — standardize, reshape, and normalize messy data before it hits your pipeline. Built by Ben Severn.

Works on files (CSV, Excel, Parquet), cloud storage (S3, GCS), or live databases. Zero-config mode auto-detects what needs fixing. One command to clean what GoldenCheck found and prep what GoldenMatch needs. Available in Python and TypeScript with full feature parity.

View the full README on GitHub

Details

Repository: github.com/benseverndev-oss/goldenflow
Website: benseverndev-oss.github.io/goldenflow
Categories: Cloud & Infrastructure, Data & Analytics, Productivity & Office
Package: goldenflow
Transport: STDIO, HTTP
Registry: MCP registry, active
Tools verified: Jun 10, 2026

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GoldenFlow

Install

Tools

Readme

GoldenFlow

Details

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