GoldenMatch

v1.4.7 Feature

This release adds 2 notable features for engineering teams evaluating rollout.

Published 3mo Data Pipelines & ETL

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✓ No known CVEs patched

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✓ No known CVEs patched in this version

Topics

data-cleaning data-engineering data-matching data-quality deduplication entity-resolution

+14 more

fellegi-sunter fuzzy-matching knowledge-graph llm master-data-management mcp-server polars pprl python record-linkage rust splink typescript zero-config

Summary

AI summary

Updates What's New, Why this matters, and accuracy/recall/balanced across a mixed release.

Full changelog

What's New

MCP Resources (4)

Clients can now read live state from GoldenMatch without calling tools:

| URI | Description |
|---|---|
| goldenmatch://dataset/stats | Record count, cluster count, match rate, pair count |
| goldenmatch://dataset/clusters | Top 50 clusters by size with member IDs |
| goldenmatch://config/current | Active matchkeys, thresholds, scorers, blocking rules |
| goldenmatch://dataset/schema | Column names, types, and sample values |

Resources are contextual — only listed when data is loaded.

MCP Prompts (5)

Guided workflows that chain the right tools in the right order:

| Prompt | Description |
|---|---|
| deduplicate-walkthrough | Full ER pipeline: profile → configure → run → review → export. Optional focus param (accuracy/recall/balanced). |
| investigate-cluster | Deep-dive a cluster: view members → explain matches → fix bad merges → shatter if needed. |
| compare-records | Field-by-field pair comparison with score breakdown and plain-English verdict. |
| data-quality-audit | Profile data → scan issues → recommend cleaning → suggest transforms. |
| pprl-setup | Guide through privacy-preserving linkage: assess sensitivity → configure → run → compare. |

Why this matters

Resources let MCP clients (Claude Desktop, Cursor, etc.) inspect GoldenMatch state passively — no tool calls needed for read-only queries.
Prompts lower the barrier to complex workflows. Instead of knowing which of 30 tools to call and in what order, users select a prompt and the LLM follows the guided sequence.

Full Changelog

https://github.com/benzsevern/goldenmatch/compare/v1.4.5...v1.4.7

View diff on GitHub

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Earlier breaking changes

v3.1.0 `GOLDENMATCH_FRAME=polars` now requires the `[polars]` extra; raises error without it.
vgoldencheck-v3.0.0 `inferred_type` emits neutral dtype vocabulary (str/int/uint/float/date/datetime/bool/other) instead of raw Polars dtypes.
vgoldencheck-v3.0.0 'inferred_type' now emits a neutral dtype vocabulary instead of raw Polars dtype strings.
vgoldencheck-v3.0.0 `scan_file`, `scan_dataframe`, and CLI `check` now run without Polars, using Arrow-native pyarrow.Table.
v3.0.0 Result frames now return pyarrow.Table instead of Polars DataFrame.