How to Use the Fauna (Serverless DB) MCP in Mastra AI

Q: Does Mastra AI support tool approval for Fauna (Serverless DB) queries?

Yes. Enable requireToolApproval in your client config. Every query will pause for your review before the agent hits the database.

Build resilient database workflows with Fauna (Serverless DB) and the Mastra AI agent framework.

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Connect Fauna (Serverless DB) MCP to Mastra AI

Create your Vinkius account to connect Fauna (Serverless DB) 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 Fauna (Serverless DB) with Mastra AI

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Automated workflows with Fauna (Serverless DB)

Use `execute_fql` inside your Mastra agents to trigger multi-step database tasks. If a query fails, the framework handles the retry logic automatically. Build reliable sequences like order processing or user verification. Your agent handles the logic, and the database keeps the state consistent.

Conditional database branching

Mastra agents decide when to query your database based on workflow state. You can branch your logic: check a balance, update a flag, or notify an admin based on the query result. It makes your database interaction part of a larger, smarter process. You stop writing rigid scripts and start building systems that react to data.

Human-in-the-loop database modifications

Require approval before any `execute_fql` command runs. This keeps you in control of critical database writes while letting your agents do the heavy lifting. You see the proposed query, verify it, and click approve. The agent then executes the FQL against your Fauna (Serverless DB) instance securely.

Setup guide

Set up Fauna (Serverless DB) 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 Fauna (Serverless DB) 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: "fauna-serverless-db-mcp-client",
  servers: {
    "fauna-serverless-db-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

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

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Common questions about Fauna (Serverless DB) MCP in Mastra AI

Add the MCP server to your agent's tool list. You can then invoke `execute_fql` as a step in any complex workflow.

Absolutely. Use the database as your source of truth for agent memory and workflow progress across multiple executions.

Configure exponential backoff in your Mastra agent. The framework will automatically retry the `execute_fql` call if it encounters a transient error.

Yes. Enable `requireToolApproval` in your client config. Every query will pause for your review before the agent hits the database.

We isolate your database operations within the MCP sandbox. Every interaction is logged and encrypted, ensuring your collection records remain private.

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