152-FZ personal data anonymizer MCP

mcp-152fz-anonymizer

An MCP server and HTTP API that find and mask personal data in text under Russia's 152-FZ before it reaches an LLM or an outside service

  • 5 ★ on the repository
  • Last commit
  • MIT
MCP server

Extended access

Why this level

  • Processes text containing sensitive personal data
  • A network misconfiguration could expose the service externally
All reasons and checks
Russian stack

pioneer113/mcp-152fz-anonymizer

Install

Services

Manual install

docker-compose up --build -d

Starts the HTTP API on port 8005; the key goes into api_keys.json.

Access and checks

How we review

Extended accessThe tool runs code or makes network calls and only reads external data.

  • Processes text containing sensitive personal data
  • A network misconfiguration could expose the service externally

This is third-party code. Review the repository files before installing.

What it does

The service detects passports, SNILS, INN, bank cards, phone numbers, emails, IP addresses, geodata and over twenty other categories in text, using Microsoft Presidio with the spacy ru_core_news_lg model plus regex rules for Russian documents. Matches are replaced with placeholders like PERSON or PASSPORT_RF. It runs in two modes: as an MCP server for Claude Desktop and Cursor, or as a standalone FastAPI HTTP service for n8n and webhook integrations. It deploys in Docker as an unprivileged user with a read-only filesystem.

Who it is for. For developers and legal staff who need to strip customer personal data out of text before sending it to a cloud model or a third-party service.

Good fit when

  • You need to strip names, passports and phone numbers before sending customer requests to a cloud LLM
  • You need to anonymize logs or exports before handing them to a contractor
  • You need automatic PII masking inside an n8n scenario or a webhook

Not a fit when

  • You need a legal guarantee of full 152-FZ compliance: the tool reduces risk but is not a certified protection measure
  • Data must never leave your perimeter at all: that needs a fully offline setup, not an MCP connection to a cloud agent

Example request

Anonymize this customer message before I send it for analysis: strip out the name, phone number and passport data

MCP

Transport
stdio
Authentication
not required

Environment variables

X-API-Key secret
HTTP API access key, set in api_keys.json; not documented for MCP mode.

Limitations

Detection relies on regex and a spacy model, so misses and false positives are possible; results are worth spot-checking against real data. The service does not store processed data, but a misconfigured firewall could expose port 8005 externally. An API key is required for HTTP mode; the README does not document a separate key setup for MCP mode.

How to disable. Stop the container (docker-compose down) and remove the server from your MCP client config.

FAQ

Does the server store the data it processes?

No, the README describes it as stateless: processed text is not logged or saved.

Which mode connects to Claude Desktop more easily?

MCP mode: install dependencies locally and run mcp run main.py, no Docker needed.

Discussion

No questions or reviews yet.

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README in short

The Russian README with an English section shows the architecture as a diagram: a request goes through a proxy into a Docker container where FastAPI calls Presidio with a spacy model and regex rules. It gives a table of data categories with examples and replacements, a Docker quick start with a curl example, and separate instructions for local development in MCP mode. The security section lists container isolation, API-key-only access and no data logging.

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