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Veilig AI-gebruik via MCP Server

Ontwikkelaars gebruiken Claude Desktop en Cursor IDE dagelijks met productiecode en gevoelige gegevens. De MCP Server-architectuur beschermt PII voordat het de AI-provider bereikt.

February 22, 20267 min lezen
MCP ServerClaude DesktopCursor IDEsecure AIdeveloper tools

Het MCP-beveiligingsprobleem

Model Context Protocol (MCP) servers verbinden AI-assistenten zoals Claude Desktop en Cursor IDE met externe tools en gegevensbronnen. Ontwikkelaars gebruiken ze om code te debuggen, databases te bevragen en documenten te analyseren — allemaal met hulp van AI.

Het probleem: wanneer ontwikkelaars gevoelige gegevens in die workflows invoeren, bereikt die data de AI-provider in leesbare vorm. Productiedatabaseschema's, klantnamen in logbestanden, API-sleutels in code — al die inhoud gaat naar externe servers wanneer de ontwikkelaar om hulp vraagt.

Hoe MCP Server Anonimisering Werkt

De anonym.legal MCP Server plaatst een transparante proxy in de dataflow. Voordat tekst de AI-provider bereikt, worden PII-elementen gedetecteerd en door tokens vervangen.

Stap 1 — Onderschepping: De MCP Server vangt alle tekst op die naar de AI-tool gaat.

Stap 2 — Detectie: Het PII-detectiesysteem identificeert gevoelige entiteiten: namen, e-mailadressen, telefoonnummers, nationale identiteitsnummers, medische nummers, financiële gegevens.

Stap 3 — Tokenisering: Elke entiteit wordt vervangen door een gestructureerd token. [NAAM_1], [EMAIL_1], [BSN_1]. De AI-provider ziet tokens, niet de echte waarden.

Stap 4 — AI-verwerking: De AI-tool verwerkt de getokeniseerde versie.

Stap 5 — Herstel: De MCP Server vervangt tokens door de originele waarden in de definitieve uitvoer.

Use Cases voor Ontwikkelaars

Code debuggen: Logbestanden met klantgegevens worden geanonimiseerd voordat ze de AI-provider bereiken.

Databaseanalyse: Schema's met klanttabelstructuren worden geanonimiseerd.

Documentreview: Contracten met partijnamen worden verwerkt met tokens.

API-integratie: Authenticatieheaders met API-sleutels worden gedetecteerd en verwijderd.

Bekijk de MCP Server installatiepagina voor setup-instructies en de beveiligingspagina voor architectuurdetails.

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Klaar om uw gegevens te beschermen?

Begin met het anonimiseren van PII met 285+ entiteitstypen in 48 talen.

Start Gratis ProefperiodeBekijk Kenmerken

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.

Related reading

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 servers live in Falkenstein, Germany.

We use Hetzner. They hold 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.