How to Use the Weblate MCP in Mastra AI

Q: How do I manage roles with Weblate and Mastra AI?

You use createrole to define a new permission set, then you associate that role with a group using the addgrouproles tool. The workflow engine ensures these steps run in the correct order.

Q: Does Mastra AI handle Weblate's project repository status?

Yes, it does. You can call getprojectrepository to check the overall VCS status. If the agent detects a stale repo or an outstanding commit, it automatically executes cleanup operations.

Q: What if I need to update user details for Weblate using Mastra AI?

You call updateuser with new credentials. If the API returns an error (e.g., invalid email format), Mastra AI catches it, logs the failure, and provides a clear path to fix the data.

Q: Can I list all Weblate projects using Mastra AI?

The listprojects tool fetches everything. Because of its built-in retry logic, it's highly reliable for fetching large datasets without timing out or losing data.

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Create your Vinkius account to connect Weblate 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 Weblate with Mastra AI

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Automate VCS Operations using the MCP Server

Use `perform_repository_operation` to handle entire version control cycles. Your agent can automatically pull, commit changes, and push updates if a conflict is detected. This handles complex multi-step operations reliably. Mastra AI's built-in retry logic means that if the initial push fails due to network jitter, the whole workflow doesn't crash; it backs off and tries again.

Structure Admin Workflow with Mastra AI

Setting up new teams is simple. The `create_group` tool makes a group, then you associate necessary permissions using `add_group_roles`. It's a reliable sequence of actions. The workflow engine handles the dependency: it won't try to assign roles until the group has been successfully created in Weblate.

Check User Health with Mastra AI

The `get_user_statistics` tool pulls detailed contribution data, showing how many translations a user owns. You can also list all users via `list_users`. This checks the current state of contributors. If an agent needs to check contributor status across fifty projects, Mastra AI guarantees that even if some API calls fail, it reports *which* ones failed and retries until the goal is met.

Setup guide

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

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

const result = await agent.generate(
  "List recent Weblate 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 Weblate. 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 Weblate MCP in Mastra AI

You use `create_role` to define a new permission set, then you associate that role with a group using the `add_group_roles` tool. The workflow engine ensures these steps run in the correct order.

Yes, it does. You can call `get_project_repository` to check the overall VCS status. If the agent detects a stale repo or an outstanding commit, it automatically executes cleanup operations.

You call `update_user` with new credentials. If the API returns an error (e.g., invalid email format), Mastra AI catches it, logs the failure, and provides a clear path to fix the data.

The `list_projects` tool fetches everything. Because of its built-in retry logic, it's highly reliable for fetching large datasets without timing out or losing data.

The server touches user account details (IDs and status), group definitions, and project metadata. It deals with structural information about who can do what within the translation ecosystem.

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