How to Use the Regex Toolkit MCP in Vercel AI SDK
Stream deterministic regex validation and PII masking directly to your Next.js UI using the Vercel AI SDK.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Regex Toolkit MCP to Vercel AI SDK
Create your Vinkius account to connect Regex Toolkit to Vercel AI SDK — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.
Key Capabilities
Stream raw text extraction directly to your Vercel AI SDK UI
Stop waiting for an LLM to finish thinking before you show data. Connect the `extract_pattern` tool to your streaming text pipeline so your users see emails, URLs, and phone numbers pop up on the screen instantly. Your Next.js edge functions run this MCP Server to parse massive text blocks without blocking the main thread. The parsed results feed into your UI components in real-time, giving you speed that raw model generations can never match.
Redact sensitive PII in real-time edge streaming
Secure user inputs before they ever hit your database or a third-party model. The `mask_sensitive_data` tool swaps out phone numbers and email addresses with standard redacted tags inside your Vercel AI SDK application. Because this runs as a native tool call during the streaming lifecycle, you catch sensitive strings early. Your frontend shows the safe, redacted version of the text to the user immediately, keeping your data pipeline clean.
Stop model hallucinations with strict validation
Models are bad at verifying format structures, so we offload that work. This MCP Server lets your agent call the `validate_pattern` tool to confirm if a string is a real email or URL before accepting it. If the validation fails, your Vercel AI SDK agent gets a hard boolean rejection. It can then prompt the user to correct the input in the chat box, preventing broken data from corrupting your database.
Set up Regex Toolkit MCP in Vercel AI SDK
Prerequisites
- Node.js 18+ and a TypeScript project
-
ai+@modelcontextprotocol/sdkpackages - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Run
npm install ai @modelcontextprotocol/sdkplus your preferred model provider (e.g.@ai-sdk/openai). - 2
Create the Streamable HTTP transport
Use
StreamableHTTPClientTransportwith your Vinkius endpoint URL. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. - 3
Discover and use tools
Call
mcpClient.tools()to auto-discover all Regex Toolkit tools. Pass them directly togenerateText()orstreamText()— no manual schema definitions needed. - 4
Works with any model provider
Swap
openai("gpt-4o")for any AI SDK provider — Anthropic, Google, Mistral. The MCP tools work identically across all supported models.
import { experimental_createMCPClient as createMCPClient } from "ai";
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";
const transport = new StreamableHTTPClientTransport(
new URL("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
);
const mcpClient = await createMCPClient({ transport });
const tools = await mcpClient.tools();
const { text } = await generateText({
model: openai("gpt-4o"),
tools,
prompt: "List recent Regex Toolkit transactions",
});
console.log(text);
await mcpClient.close(); Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by regex-toolkit. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Common questions about Regex Toolkit MCP in Vercel AI SDK
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