Regex Toolkit

Regex Toolkit MCP Connector for Claude

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Equip your AI with strict Regular Expressions. Deterministically extract, validate, and redact Emails, URLs, and Phones without hallucinations.

3 tools Official Updated Jun 28, 2026 Official Vinkius Partner

Parsing unstructured text to find contact information is a classic LLM vulnerability. AI models often "guess" email boundaries or invent fake phone numbers when summarizing text. The Regex Toolkit MCP enforces strict mathematical patterns to guarantee 100% extraction and validation accuracy.

The Superpowers

  • Flawless Extraction: Pull every single valid Email, URL, or Phone number from a giant block of text instantly into a clean JSON array.
  • Zero-Trust Validation: Ensure that user inputs are structurally perfect before passing them to external databases or CRMs.
  • PII Redaction Engine: Instantly mask sensitive client data ([EMAIL_REDACTED]) before generating public reports or passing context to unsecure layers.
  • Privacy First (Local): Your data never leaves your infrastructure. The regex engine compiles and executes entirely locally.
regexdata-redactioninput-validationpattern-matchingdata-sanitizationsecurity

3 tools expose this connector's capabilities to your AI agent.

mask_sensitive_data

Redacts sensitive PII (emails, phones, URLs) from a text blob by replacing them with [REDACTED] tags

validate_pattern

Validates if a single string perfectly matches an email, URL, or phone format

extract_pattern

Extracts all unique emails, URLs, or phone numbers from a large body of text

See how to talk to your AI agent using Regex Toolkit.

Extract all email addresses from this massive support ticket transcript.

Using the extract_pattern tool (type='email'): I found 3 unique emails: ['user@gmail.com', 'admin@company.net', 'billing@startup.io'].

Mask all sensitive phone numbers and emails in this document before I save it to the public database.

Using the mask_sensitive_data tool: The sanitized text is: 'Contact [EMAIL_REDACTED] or call [PHONE_REDACTED] for support.'

Verify if 'https://www.vinkius.com/dashboard?user=123' is a mathematically valid URL.

Using the validate_pattern tool (type='url'): Yes, it is a perfectly valid URL structure.

Because LLMs predict text probabilistically. They might miss emails embedded in weird characters (like `contact@company.com.` with a trailing dot) or hallucinate non-existent addresses. Regex provides mathematical certainty.

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