How to Use the DocBreach MCP in Mastra AI

Build resilient documentation-aware agents in Mastra AI with automated content discovery and extraction.

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Connect DocBreach MCP to Mastra AI

Create your Vinkius account to connect DocBreach to Mastra AI 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 Mastra AI

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Automated discovery for Mastra AI workflows

Mastra AI agents need reliable inputs to make decisions. `docs.discover` locates the documentation for your target service, giving your workflow engine a clear starting point. This avoids hardcoding URLs. Your Mastra AI agent dynamically finds the latest docs, ensuring your automated workflows don't break when documentation links change.

Extracting schema for complex agent logic

Complex tasks require precise API knowledge. Use `docs.extract` to pull structured endpoint definitions from OpenAPI or Postman specs directly into your Mastra AI agent memory. You then use these definitions for conditional branching. If the agent knows the exact request format, it can retry failed calls with the correct parameters without human intervention.

Reading technical specs for agent execution

Your Mastra AI agent needs to read the fine print. `docs.read` converts complex HTML or PDF specs into clean Markdown that the agent can interpret during a task. It also identifies related documentation links. This allows your Mastra AI agent to navigate through auth guides and setup pages autonomously, completing multi-step tasks in one go.

Setup guide

Set up DocBreach MCP in Mastra AI

Prerequisites

Node.js 18+ and a TypeScript project
@mastra/mcp + @mastra/core packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run npm install @mastra/mcp @mastra/core plus your preferred model provider (e.g. @ai-sdk/openai).
2

Configure the MCPClient
Create an MCPClient with your Vinkius endpoint as a URL object. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and inject tools
Call mcpClient.listTools() and spread the result into your agent's tools object. All DocBreach tools become native Mastra tools.
4

Run with any model
Swap openai("gpt-4o") for any AI SDK-compatible provider. Call agent.generate() and the agent routes tool calls through MCP automatically.

agent.ts

import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";

const mcpClient = new MCPClient({
  id: "docbreach-mcp-client",
  servers: {
    "docbreach-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "DocBreach Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to DocBreach tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent DocBreach transactions"
);
console.log(result.text);

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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 Mastra AI

You register the server in your Mastra AI agent configuration. Once registered, the tools become available for your workflow, allowing the agent to call `docs.discover` or `docs.read` as needed.

Mastra AI workflows can catch errors from the MCP Server. If `docs.read` fails to return content, your agent can trigger a fallback path or log the error for your review.

It is highly reliable for standard documentation sites. By providing specific queries to `docs.discover`, your Mastra AI agent narrows down the exact documentation source quickly.

No. The server fetches content on demand for the current task. Your Mastra AI agent uses the data in memory, and the server does not persist your documentation requests.

It handles HTML, JSON, YAML, OpenAPI specs, Postman Collections, PDFs under 5MB, and llms.txt. This covers almost every standard format your Mastra AI agent will encounter.

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