By · Last updated 2026-06-30

REST API + MCP Server

PII Anonymization API for Developers

An anonymization API is a developer endpoint that strips PII from text inside your own pipelines. Ship privacy-first applications with anonym.legal's REST endpoints for CI/CD integration, MCP Server for AI tools, and consistent anonymization across 48 languages.

285+
Entity types
48
Languages
200
Free tokens/month

挑战

开发团队在真实测试数据与数据保护之间始终面临矛盾:

  • 生产数据包含敏感 PII,无法直接使用
  • 合成数据通常缺乏有效测试所需的真实感
  • 手动匿名化耗时且容易出错
  • 不同环境需要一致、可重现的数据
# Anonymize test data in CI/CD pipeline
curl -X POST https://anonym.legal/api/presidio/anonymize \
  -H "Authorization: Bearer $API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"text": "Contact john@company.com", "anonymizers": {"DEFAULT": {"type": "replace"}}}'

解决方案

通过我们的 RESTful API 将 PII 匿名化直接集成到您的开发工作流中。

REST API

简洁的 JSON API,可集成到任何技术栈。在单次请求中完成分析和匿名化。

CI/CD 就绪

在流水线中自动化测试数据生成。每次输出结果一致。

可重现

相同输入,相同输出。确定性结果,保障可靠测试。

高速

每分钟处理数千条记录。无需 GPU。

API Endpoints

Simple REST API with bearer token authentication. Integrate in minutes.

EndpointMethodDescription
/api/presidio/analyzePOSTDetect PII entities in text
/api/presidio/anonymizePOSTAnonymize detected entities
/api/imagePOSTRedact PII from images
/api/structuredPOSTProcess CSV/Excel files
/api/presidio/entitiesGETList supported entity types

Integration Options

REST API

Standard REST endpoints with JSON payloads. Works with any language or framework.

  • Bearer token authentication
  • Batch processing support
  • Webhook callbacks (Pro+)

MCP Server

Model Context Protocol integration for AI tools like Claude Desktop and VS Code.

  • analyze, anonymize, deanonymize tools
  • estimate_cost for pricing transparency
  • Multi-language support in tool calls

Built for developers

ISO 27001 Aligned
Germany (EU) Hosted
Bearer Token Auth
REST + MCP

立即开始构建

每月 200 个免费令牌。完整文档可供查阅。

Limitations / Important note

  • Rate limits and endpoint availability depend on your plan; build in retry/backoff handling.
  • Detection results are probabilistic; validate before automated downstream use. This is not legal advice.

How we measure — our methodology

About this page

We update this page when our platform or the law changes.

Read our founder note for how we work.

Each change shows up in the timestamp at the top.

We follow these rules

  • GDPR (EU 2016/679).
  • ISO/IEC 27001:2022.
  • NIS2 (EU 2022/2555).
  • HIPAA safe harbor under 45 CFR § 164.514(b)(2).

Our promise

We do not sell your data.

We do not train models on your text.

We store your files in Germany.

You can delete your account at any time.

You own your work.

Where we run

Our company HQ is in Saarbrücken, Germany. Our servers run in Hetzner's Falkenstein datacenter.

Hetzner holds ISO 27001 certification.

All data stays in the EU.

Backups run every day.

Need help?

Email support@anonym.legal.

We reply within one business day.

How we test

We run a full check suite on every release.

Each surface gets its own sweep script and report.

Human reviewers spot-check the output each week.

We track recall and precision on a labelled set.

Bad runs block the deploy.

What we never do

  • We never sell your information to third parties.
  • We never train models on what you upload.
  • We never keep your work after you delete it.
  • We never share keys with any outside firm.
  • We never run ads inside the product.

Plans in plain words

We sell credits, not seats.

One credit covers one short job.

Long jobs use a few credits each.

You can top up at any time.

Unused credits roll over each month.

Read the plans page for current rates.

Who built this

A small team of engineers and lawyers built this.

We ship from Europe and work in the open.

Our founder note spells out why we started.

Where to start

How the parts fit

A browser add-on cleans text inside Chrome.

A Word plug-in handles drafts in Office.

A small desktop tool works on whole folders.

An agent protocol link feeds large models safely.

All four share one core engine and one rule set.

Words from our team

We started this work after a lunch about cookies.

One friend kept getting odd ads on her phone.

We asked why a court file leaked through a draft.

We sketched the first build on a napkin that week.

By month three we had a tiny demo for a friend.

She used it on her first case the next day.

Common questions we hear

Can the tool read scanned PDFs? Yes, with OCR.

Does it work on long files? Yes, in small chunks.

Can I roll my own rule set? Yes, save it as a preset.

Does it run offline? The desktop build runs offline.

Do you keep my files? No, the cloud build wipes after each run.

Will it learn from my work? No, we never train on inputs.

A short tour of the workflow

Upload a file or paste a snippet of prose.

Pick the entities you want gone from the draft.

Choose a method: replace, mask, hash, encrypt, or redact.

Press run and watch the side panel show each hit.

Skim the result and tweak any rule that misfired.

Save the cleaned file or send it to a teammate.