How to Use the Regex Toolkit MCP in LangChain

Chain Regex Toolkit tools in LangChain pipelines to parse and sanitize data without hallucinating.

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Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers — Included with Plan

Connect Regex Toolkit MCP to LangChain

Create your Vinkius account to connect Regex Toolkit to LangChain — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

GDPR Included with Plan

Setup Regex Toolkit with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity Vinkius runs on Gemini

Gemini

Grok

Deterministic data extraction for LangChain

The `extract_pattern` tool pulls emails, URLs, and phone numbers from raw text. It turns unstructured logs into clean, structured data for your next chain link. You don't guess what the text contains. You get exact matches that your agent can pass directly to a database or API.

PII redaction in LangChain workflows

Use `mask_sensitive_data` to scrub PII before passing text to an LLM. It replaces sensitive patterns with [REDACTED] tags, keeping your pipelines secure. This is a critical step when you're dealing with logs or user input. It ensures you never accidentally send private data to external models.

Input validation for LangChain agents

The `validate_pattern` tool checks if a string matches your expected format. It provides a simple boolean response, letting your agent decide if it should proceed or request a retry. It removes the need for custom validation logic in your code. The agent checks the format, confirms it's valid, and moves on.

Setup guide

Set up Regex Toolkit MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes Regex Toolkit tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "regex-toolkit-mcp": {
        "transport": "http",
        "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    }
}) as client:
    tools = client.get_tools()

    agent = create_react_agent(
        ChatOpenAI(model="gpt-4o"),
        tools,
    )
    result = await agent.ainvoke({
        "messages": "List recent Regex Toolkit transactions"
    })
    print(result["messages"][-1].content)

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