How to Use the DocBreach MCP in Vercel AI SDK

Q: How do I search for API credentials using DocBreach with the Vercel AI SDK?

Use docs.search with the site parameter set to your target documentation URL. This limits the scope to the official docs, ensuring your Vercel AI SDK agent finds valid authentication methods instead of community noise.

Q: Can I map an entire API site for my Vercel AI SDK project?

Yes. The docs.map tool creates a structure of the entire documentation site. Your agent can then read specific sections to understand the API architecture without scanning every page.

Stream raw documentation data into your Vercel AI SDK frontends for real-time AI responses without the wait.

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Connect DocBreach MCP to Vercel AI SDK

Create your Vinkius account to connect DocBreach to Vercel AI SDK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup DocBreach with Vercel AI SDK

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Direct documentation ingestion for Vercel AI SDK

Your Vercel AI SDK frontend needs clean data. DocBreach uses `docs.read` to fetch raw content and push it straight into your stream, bypassing the lag of browser rendering. Since this MCP Server operates over HTTP, your Edge Functions stay fast. The AI client receives clean Markdown immediately, letting your UI update while the agent parses the logic.

Mapping API structures for AI-generated code

Stop guessing the endpoint hierarchy. Use `docs.map` to generate a full table of contents for any service, then feed that structure to your agent to build accurate API calls. Once the structure is clear, `docs.extract` pulls the specific OpenAPI or Postman specs you need. It turns chaotic documentation into a predictable schema that your Vercel AI SDK agent can actually execute.

Targeted documentation discovery

Searching for the right docs shouldn't involve trial and error. `docs.discover` finds the relevant source material based on your specific implementation requirements. After finding the right site, use `docs.search` to find authentication headers or specific endpoints within the domain. Your Vercel AI SDK agent gets the exact context it needs to generate working code on the first try.

Setup guide

Set up DocBreach MCP in Vercel AI SDK

Prerequisites

Node.js 18+ and a TypeScript project
ai + @modelcontextprotocol/sdk packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies

Run npm install ai @modelcontextprotocol/sdk plus your preferred model provider (e.g. @ai-sdk/openai).
2

Create the Streamable HTTP transport

Use StreamableHTTPClientTransport with 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 DocBreach tools. Pass them directly to generateText() or streamText() — 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.

index.ts

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 DocBreach transactions",
});

console.log(text);
await mcpClient.close();

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by DocBreach. 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 DocBreach MCP in Vercel AI SDK

Use `docs.search` with the site parameter set to your target documentation URL. This limits the scope to the official docs, ensuring your Vercel AI SDK agent finds valid authentication methods instead of community noise.

No. It fetches raw text and Markdown directly, which is why it works perfectly within the Vercel AI SDK's streaming architecture. You avoid the overhead of heavy headless browsers entirely.

Yes. The `docs.map` tool creates a structure of the entire documentation site. Your agent can then read specific sections to understand the API architecture without scanning every page.

DocBreach processes text-based documentation only. It does not store your local data or transmit your API keys, keeping your Vercel AI SDK environment isolated.

The server needs network access to the documentation URL. If your Vercel AI SDK environment is heavily restricted, you will need to whitelist the endpoint for the DocBreach MCP server.

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