How to Use the GroundX MCP in Mastra AI

Q: Does Mastra AI handle human-in-the-loop approvals for GroundX tools?

Yes, you can enable requireToolApproval on any GroundX tool. This pauses the Mastra AI agent until a human reviews the action.

Q: Can I search across multiple buckets in Mastra AI?

The searchcontent tool performs a global search across all your buckets. You can filter results by metadata if you need to narrow the scope.

Build resilient RAG pipelines in Mastra AI by chaining GroundX tools with automated retries and conditional branching.

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Connect GroundX MCP to Mastra AI

Create your Vinkius account to connect GroundX 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 GroundX with Mastra AI

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Workflow-ready RAG in Mastra AI

Incorporate `search_content` into your agentic workflows to handle complex queries that require multi-step verification. Mastra AI executes these as atomic steps, allowing you to build logic that branches based on search relevance. If a search returns low-confidence results, your agent can trigger a secondary crawl using `ingest_website`. This ensures your agent always has the context it needs before it provides an answer to the user.

Resilient ingestion pipelines

Use `ingest_documents` as a core step in your automated agent tasks. Because Mastra AI supports exponential backoff, you can wrap these ingestion calls to ensure your data makes it into the bucket even if the network blips. Your agents can monitor these tasks by calling `get_ingest_status` in a loop. If a job hangs, the agent handles the error gracefully without crashing your entire pipeline.

Multi-tenant data isolation

Manage user-specific data by programmatically generating buckets with `create_bucket` for each new agent session. This keeps your search scope tight and relevant to the current user context. You can use `list_groups` to manage these partitions at scale. It prevents cross-contamination of data and ensures your search results stay within the boundaries of the active workflow.

Setup guide

Set up GroundX 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 GroundX 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: "groundx-mcp-client",
  servers: {
    "groundx-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

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

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Common questions about GroundX MCP in Mastra AI

You register the GroundX server in your agent configuration and spread the tools into your agent's toolset. Then, you simply call `search_content` within your workflow steps.

Yes, you can enable `requireToolApproval` on any GroundX tool. This pauses the Mastra AI agent until a human reviews the action.

You build a retry policy into your workflow. The agent checks `get_ingest_status`, and if it reports an error, the agent can re-attempt the ingestion automatically.

The `search_content` tool performs a global search across all your buckets. You can filter results by metadata if you need to narrow the scope.

All ingested content is encrypted at rest within your private bucket. Only agents with your specific endpoint token can trigger tools to read these files.

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