How to Use the Haystack (deepset Cloud) MCP in Mastra AI

Build resilient RAG workflows in Mastra AI by connecting your Haystack (deepset Cloud) index to automated agent branching.

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Connect Haystack (deepset Cloud) MCP to Mastra AI

Create your Vinkius account to connect Haystack (deepset Cloud) 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 Haystack (deepset Cloud) with Mastra AI

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Automated RAG pipeline branching

Integrate `run_pipeline` into your Mastra AI workflows to handle complex logic. If a search returns low-confidence results, you can branch your agent to try a different query. This setup allows for robust error handling. You set the rules, and the agent executes the search, retrying automatically if the connection flickers.

Direct index search with Mastra AI

Use `search_documents` to give your agents immediate access to your knowledge base. The agent fetches relevant context, processes it, and generates a response based on your specific documents. It removes the need for manual data scraping. Your agent simply asks the index for what it needs and gets the answer back in structured text.

Workspace and pipeline observability

Monitor your infrastructure state by calling `list_workspaces` and `get_pipeline` within your workflow code. You can ensure the right pipeline is active before running tasks. This visibility prevents runtime failures. If a workspace is missing or a pipeline is inactive, your agent can catch it before the execution starts.

Setup guide

Set up Haystack (deepset Cloud) 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 Haystack (deepset Cloud) 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: "haystack-deepset-cloud-mcp-client",
  servers: {
    "haystack-deepset-cloud-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

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

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Common questions about Haystack (deepset Cloud) MCP in Mastra AI

You install the client and pass the server URL into your agent configuration. Once the MCP tools are registered, you can call `search_documents` as a native tool within your agent definition.

Yes. You can configure your Mastra AI workflow with retry logic around any tool call. If the connection to your deepset Cloud pipeline fails, the agent will handle the attempt automatically.

By enabling tool approval in your agent, you can pause execution before `run_pipeline` fires. This lets you inspect the search parameters before the agent touches your documents.

The server connects via secure transport. Your documents are queried in real-time, and no data is cached or stored by the agent framework itself during the process.

The server exposes metadata such as file names, IDs, and statuses via `list_files` and `get_file`. It allows your agents to inventory your documents before deciding which ones to search.

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