mcpField
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GoldenPipe

GoldenPipe

Remote
benseverndev-oss.github.ioData & Analytics0Updated 26w ago

About GoldenPipe

GoldenPipe is a Python orchestrator for profiling data quality, transforming records, and deduplicating them into golden records. It is for data teams that want one adaptive pipeline, with decisions explained and privacy-preserving matching available.

Key features

  1. 01Profile data quality
  2. 02Transform and standardize records
  3. 03Deduplicate and match records
  4. 04Skip unnecessary transformations
  5. 05Route sensitive fields to privacy-preserving matching
  6. 06Explain pipeline decisions

Use cases

  1. 01Cleaning and deduplicating customer CSVs
  2. 02Running checks and matching without transformations
  3. 03Matching records that contain sensitive fields

MCP support

GoldenPipe offers a hosted MCP server and a locally runnable server. Its four tools list pipeline stages, validate wiring, run the full pipeline, and explain configurations.

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://goldenpipe-mcp-production.up.railway.app/mcp/
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

Packages
pypigoldenpipe1.5.0

Tools

Details

From the project README

Moved. This repo has moved into the benzsevern/goldenmatch monorepo at packages/python/goldenpipe/. This repo is archived; new development happens in the monorepo.

GoldenPipe

Golden Suite orchestrator -- Check quality, fix issues, deduplicate records. One command. Built by Ben Severn.

PyPI CI codecov Downloads Python 3.11+ License: MIT Docs DQBench Pipeline Open In Colab

What It Does

Raw Data
  | GoldenCheck   -- profile & discover quality issues
  | GoldenFlow    -- fix issues, standardize, reshape
  | GoldenMatch   -- deduplicate, match, create golden records
  v
Golden Records

GoldenPipe orchestrates the full pipeline with adaptive logic:

  • Skips transformation if no quality issues found
  • Routes to privacy-preserving matching if sensitive fields detected
  • Reports reasoning for every decision

Install

pip install goldenpipe

Quick Start

import goldenpipe as gp

result = gp.run("customers.csv")

print(result.status)        # "success"
print(result.check)         # Quality findings
print(result.transform)     # What was fixed
print(result.match)         # Deduplicated clusters
print(result.reasoning)     # Why each decision was made

CLI

goldenpipe run customers.csv                # Full pipeline
goldenpipe run customers.csv --verbose      # Show reasoning
goldenpipe run customers.csv --skip-flow    # Check + Match only
goldenpipe run customers.csv --strategy pprl  # Force privacy mode
goldenpipe run customers.csv -o golden.csv  # Save golden records

Remote MCP Server

GoldenPipe is available as a hosted MCP server on Smithery — connect from any MCP client without installing anything.

Claude Desktop / Claude Code:

{
  "mcpServers": {
    "goldenpipe": {
      "url": "https://goldenpipe-mcp-production.up.railway.app/mcp/"
    }
  }
}

Local server:

pip install goldenpipe[mcp]
goldenpipe mcp-serve

4 tools available: list pipeline stages, validate wiring, run full check-transform-match pipeline, explain configs.

Part of the Golden Suite

ToolPurposeInstall
GoldenCheckValidate & profile data qualitypip install goldencheck
GoldenFlowTransform & standardize datapip install goldenflow
GoldenMatchDeduplicate & match recordspip install goldenmatch
GoldenPipeOrchestrate the full pipelinepip install goldenpipe

Author

Ben Severn

License

MIT

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