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datamimic MCP Server

rapiddweller/datamimic

Score: 74.0 → 0% Rank #3299 MCP Server
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Model-driven synthetic test data for CI/CD and analytics - deterministic, privacy-preserving, and domain-aware. Includes Python APIs, XML pipelines, and MCP/IDE integration to orchestrate realistic datasets for finance, healthcare, and other regulated environments.

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Overview

rapiddweller/datamimic is a Python tool licensed under MIT. Model-driven synthetic test data for CI/CD and analytics - deterministic, privacy-preserving, and domain-aware. Includes Python APIs, XML pipelines, and MCP/IDE integration to orchestrate realistic datasets for finance, healthcare, and other regulated environments. Topics: data-generation, data-privacy, data-simulation, synthetic-data, test-automation, testing, deterministic, mcp, pii, data-anonymization, data-masking, gdpr, pci-dss, seed, time-series.

Ranked #3299 out of 24846 indexed tools.

Ecosystem

Python MIT
data-generationdata-privacydata-simulationsynthetic-datatest-automationtestingdeterministicmcppiidata-anonymizationdata-maskinggdprpci-dssseedtime-series

Score Breakdown

StarsFreshnessIssue HealthContributorsDependents
Stars 15% 116

116 stars → growing community

Freshness 25% 29d ago

Last commit 29d ago → recently updated

Issue Health 25% 50%

29/58 issues closed → decent issue management

Contributors 10% 4

4 contributors → small team

Dependents 25% 0

No dependents → no downstream usage

npm Downloads N/A
PyPI Downloads N/A
Forks 3
Description Detailed
License MIT

Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →

How to Improve

Dependents medium impact

No downstream dependents detected yet — adoption by other projects is the strongest trust signal

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Matched Queries

topic:mcp

From the README

# DATAMIMIC — Governed Test Data for Regulated Enterprises

> **This repository contains the DATAMIMIC Community Edition (CE).** MIT-licensed, Python-native, MCP-ready.
>
> CE is fully usable standalone for deterministic synthetic data generation and model-based pseudonymization. The Enterprise Platform adds governed workflows, PII scanning, role-based access, audit logging, scheduling, multi-system execution, and the operational layer for governed enterprise workflows.
>
> 👉 **Enterprise Platform:** [datamimic.io](https://datamimic.io) &nbsp;|&nbsp; 📘 **Docs:** [docs.datamimic.io](https://docs.datamimic.io) &nbsp;|&nbsp; 📅 **Book a strategy call:** [datamimic.io/contact](https://datamimic.io/contact)
>
> 🤖 **AI agent?** Start at [`AGENTS.md`](https://github.com/rapiddweller/datamimic/blob/development/AGENTS.md) and use the project CLI: preserve new intent as `model.dm.json`, submit an early best attempt via `datamimic scaffold ... --format json`, repair from the structured issues,
Read full README on GitHub →

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