How to Use the Lokalise MCP in Mastra AI

Q: Can Mastra AI handle Lokalise translation orders?

Yes. You can use the listorders tool to track the status of your current requests and have the agent report back when they are finished.

Build resilient localization workflows with the Lokalise MCP Server and Mastra AI.

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Connect Lokalise MCP to Mastra AI

Create your Vinkius account to connect Lokalise 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 Lokalise with Mastra AI

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Orchestrate translation tasks with Mastra AI

Build agent workflows that handle errors automatically. If a translation push fails, Mastra AI uses `create_key` and retries the operation based on your defined logic. This setup ensures your translation pipeline keeps moving even when network hiccups occur. You get a reliable way to manage your strings without babysitting the process.

Conditional project management

Use `list_projects` to decide which project needs a new language update. You can branch your agent logic based on the output, moving to `create_project` only when necessary. It removes the guesswork from your pipeline. Your agents make decisions based on the current state of your Lokalise account, not static configurations.

Manage team access programmatically

Verify permissions with `list_team_members` before triggering bulk updates. It keeps your security posture intact while allowing your agents to operate autonomously. This tool ensures that only the right people are involved in your localization cycle. You define the rules, and the agent follows them every single time.

Setup guide

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

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

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

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Common questions about Lokalise MCP in Mastra AI

You initialize the MCP client in your agent setup and spread the tools into your agent's toolkit. It automatically handles the connection for you.

Yes. You can use the `list_orders` tool to track the status of your current requests and have the agent report back when they are finished.

It does. Because the server tools are accessible, Mastra AI can catch failures on `upload_file` and trigger a retry according to your workflow policy.

You can explicitly pick which tools to expose to your agent during the client initialization. This keeps your agent focused on specific tasks like key management.

The server interacts exclusively with your translation strings and project configurations. All communications are encrypted via the Vinkius gateway, and your data is never persisted beyond the ephemeral session.

Use it with your favorite AI tools

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