How to Use the MyScale (SQL Vector Database API) MCP in Mastra AI

Q: How do I set up MyScale (SQL Vector Database API) with Mastra AI?

Install @mastra/mcp and instantiate the client with the Vinkius URL. Spread the tools directly into your Mastra agent configuration. The framework handles transport auto-detection automatically.

Q: Can MyScale (SQL Vector Database API) trigger human-in-the-loop approvals in Mastra AI?

Yes. You can set requireToolApproval on destructive tools like createvectortable or raw executesqlquery executions. This forces the system to wait for manual confirmation before modifying your database schema.

Q: How do I handle index building errors with MyScale (SQL Vector Database API) and Mastra AI?

Trigger the build with createvectorindex and use a Mastra workflow loop to poll checkindexstatus. If the status returns an error, the workflow can trigger a retry or notify your team.

Q: Does this server support SQL joins?

Yes. You can run any complex SQL query using executesqlquery. This allows your agent to join vector search results with relational metadata in one step.

Build resilient SQL vector workflows with Mastra AI and this database MCP Server.

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Connect MyScale (SQL Vector Database API) MCP to Mastra AI

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Setup MyScale (SQL Vector Database API) with Mastra AI

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Run resilient similarity searches in Mastra AI

The `vector_search` tool handles semantic lookups and automatically structures the SQL query for your database. If a query fails due to network hiccups, Mastra AI retries the operation using its built-in exponential backoff. This gives you a reliable way to fetch document matches without writing complex retry logic. Your workflows keep running even when database connections flicker.

Build schema migrations inside agentic workflows

The `create_vector_table` tool lets your agent set up new tables with vector columns on the fly. This is useful for dynamic multi-tenant setups where you need to isolate user data into separate tables. By combining this with Mastra AI workflows, you can branch your logic based on whether a table exists or needs creation. The agent handles the schema definition and proceeds to the next step automatically.

Verify cluster health with this MCP Server

The `ping_cluster` tool checks if your database is online and accepting queries. If the database is unresponsive, your Mastra AI workflow can branch to alert an administrator instead of failing silently. This proactive checking prevents your agent from attempting expensive operations on a disconnected cluster. It keeps your system logs clean and your workflows predictable.

Setup guide

Set up MyScale (SQL Vector Database API) 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 MyScale (SQL Vector Database API) 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: "myscale-sql-vector-database-api-mcp-client",
  servers: {
    "myscale-sql-vector-database-api-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

const result = await agent.generate(
  "List recent MyScale (SQL Vector Database API) transactions"
);
console.log(result.text);

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Common questions about MyScale (SQL Vector Database API) MCP in Mastra AI

Install `@mastra/mcp` and instantiate the client with the Vinkius URL. Spread the tools directly into your Mastra agent configuration. The framework handles transport auto-detection automatically.

Yes. You can set `requireToolApproval` on destructive tools like `create_vector_table` or raw `execute_sql_query` executions. This forces the system to wait for manual confirmation before modifying your database schema.

Trigger the build with `create_vector_index` and use a Mastra workflow loop to poll `check_index_status`. If the status returns an error, the workflow can trigger a retry or notify your team.

Yes. You can run any complex SQL query using `execute_sql_query`. This allows your agent to join vector search results with relational metadata in one step.

This MCP Server processes SQL commands and database credentials inside an isolated, zero-trust V8 sandbox on Vinkius. The execution environment is completely ephemeral, meaning no query history or connection strings persist after the tool execution finishes.

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