How to Use the Azure Synapse Analytics MCP in Mastra AI

Q: How do I configure Azure Synapse Analytics with Mastra AI?

Install @mastra/mcp@latest via npm. Create a new MCPClient instance, pass your Vinkius server URL in the servers object, and spread the available tools into your agent.

Q: How do I add human-in-the-loop for Azure Synapse Analytics operations in Mastra AI?

Set the requireToolApproval property on your agent configuration. The workflow will pause and wait for manual confirmation before executing pipeline or dataset queries.

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Connect Azure Synapse Analytics MCP to Mastra AI

Create your Vinkius account to connect Azure Synapse Analytics 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 Azure Synapse Analytics with Mastra AI

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Automate Synapse pipelines with Mastra AI

The `get_pipeline` and `list_pipelines` tools plug directly into your automated workflows. When a pipeline check fails, your agent catches the error, applies exponential backoff, and attempts the read operation again automatically. You initialize the connection using `new MCPClient` and spread the returned array via `listTools()` into your agent configuration. This setup allows your system to monitor data integration tasks without manual oversight.

Monitor compute pools conditionally

Injecting `list_spark_pools` and `list_sql_pools` into your workflow engine enables strict conditional branching based on compute availability. If a serverless SQL pool drops offline, the agent evaluates the response and triggers a secondary notification path. The framework auto-detects the Streamable HTTP transport from this MCP server. Your deployment scripts push these infrastructure checks to any cloud provider with a single command.

Audit datasets and linked services

Executing `list_datasets` and `list_linked_services` gives your agents the ability to map explicit storage targets across your data warehouse. You can require human approval for these specific tool calls using the `requireToolApproval` flag. Developers combine these operations with `list_notebooks` to build complex audit trails. The system pulls Spark notebook configurations, checks linked service validity, and halts the workflow if it detects missing connections.

Setup guide

Set up Azure Synapse Analytics 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 Azure Synapse Analytics 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: "azure-synapse-analytics-mcp-client",
  servers: {
    "azure-synapse-analytics-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

const result = await agent.generate(
  "List recent Azure Synapse Analytics 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 Azure Synapse Analytics. 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 Azure Synapse Analytics MCP in Mastra AI

Install `@mastra/mcp@latest` via npm. Create a new `MCPClient` instance, pass your Vinkius server URL in the servers object, and spread the available tools into your agent.

The framework handles retries natively. If a request for pipeline definitions times out, the engine applies exponential backoff and tries the operation again.

The client automatically detects whether the endpoint uses SSE or Streamable HTTP. You just provide the URL and let the framework handle the connection details.

Set the `requireToolApproval` property on your agent configuration. The workflow will pause and wait for manual confirmation before executing pipeline or dataset queries.

Your workspace metadata never rests on our disks. The ephemeral MCP server sandbox connects, reads your SQL pool states and dataset definitions, returns the payload to your workflow, and terminates instantly.

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