goldenmatch MCP Server
benseverndev-oss/goldenmatch
[](https://agentrank-ai.com/tool/benseverndev-oss--goldenmatch/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge) Zero-config entity resolution feeding a durable identity layer: messy records from any source become stable golden entities, a Customer 360 with provenance, merge/split and audit. Fellegi-Sunter beats hand-tuned Splink. Arrow-native/Rust, 250M rows in 11.2 min. Python + edge TypeScript (WASM), SQL-native in Postgres & DuckDB, 97 MCP tools + REST.
claude mcp add agentrank -- npx -y agentrank-mcp-server Overview
benseverndev-oss/goldenmatch is a Python tool licensed under MIT. Zero-config entity resolution feeding a durable identity layer: messy records from any source become stable golden entities, a Customer 360 with provenance, merge/split and audit. Fellegi-Sunter beats hand-tuned Splink. Arrow-native/Rust, 250M rows in 11.2 min. Python + edge TypeScript (WASM), SQL-native in Postgres & DuckDB, 97 MCP tools + REST. Topics: data-engineering, data-quality, deduplication, entity-resolution, fuzzy-matching, llm, polars, python, record-linkage, pprl, mcp-server, typescript, zero-config, splink, data-cleaning, data-matching, fellegi-sunter, knowledge-graph, master-data-management, rust.
Ranked #506 out of 24846 indexed tools.
In the top 3% of all indexed tools.
Ecosystem
Score Breakdown
133 stars → growing community
Last commit 29d ago → recently updated
275/290 issues closed → responsive maintainer
4 contributors → small team
No dependents → no downstream usage
Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →
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From the README
<div align="center"> # GoldenMatch **Find the rows in your data that are the same person, company or product. No rules to write, no labelled pairs, no model to train.** Zero-config entity resolution for Python. Point it at a CSV or a table: it chooses how to match, shows you what it chose, and merges each group of duplicates into one golden record. <br> </div> > **v3.22.0: Zero-config person dedupe is 18-30x faster, and your records come back as you entered them.** 250k rows went from 520 s to 18 s with identical clusters (upgrade pulls `goldenmatch-native` 0.2.3). The unique, duplicate and deduplicated tables now carry your original values instead of standardized ones; `keep_original_values=False` or `--standardized-values` restores the old output. > > **v3.21.0: No false alarms on small files, and no LLM calls you didn't ask for.** A correct run on a small file no longer logs RED "output may be low-precision", and auto-config now turns on the (paid) LLM scorer only when you pasRead full README on GitHub →
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