How to Use the Weblate MCP in Cursor

Q: How do I use Weblate with Cursor for project status checks?

You write code that calls getprojectrepository. The AI client executes the tool and returns the live VCS output, which you can then immediately process or display in your editor’s context.

Q: Can Cursor handle complex Weblate user management?

Yes. You'll use createuser and addgrouproles to write functions that manage user lifecycles, ensuring all necessary parameters are passed directly into your code.

Q: What is the best way to get language statistics in Weblate using Cursor?

Call listprojectlanguages. The resulting JSON data—showing usage counts and progress—is then available for you to consume directly within your function’s logic.

Inject live Weblate localization data into code using the MCP Server in Cursor.

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Connect Weblate MCP to Cursor

Create your Vinkius account to connect Weblate to Cursor 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 Cursor

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Retrieve Project Metadata for Code Context

Need to write a script that checks translation status? The `get_project` tool fetches all necessary project details. Your AI client then injects this live data directly into the code block you're writing. This means your function can use real-world inputs, like calling `list_project_components` results to build a dynamic manifest.

Manage Users and Roles in Live Code

When building internal tooling, you need user context. The `get_user` tool fetches detailed user data that your agent can use. You'll write code that validates permissions using `get_role` output. It’s about making the API responses part of your source files, not just logging them out.

Perform Localization Actions via MCP Server

The agent calls `create_project` and immediately uses the returned project ID in subsequent functions. You're building workflows that execute multiple Weblate commands back-to-back. Writing code becomes much easier when you can rely on live data, like fetching a language list via `list_languages` to populate an enum.

Setup guide

Set up Weblate MCP in Cursor

Prerequisites

Cursor installed (macOS, Windows, or Linux)
Active Vinkius subscription with a valid endpoint token

1

Open MCP Settings

Go to Cursor Settings → MCP or open the Command Palette (Cmd+Shift+P / Ctrl+Shift+P) and search for "MCP: Add Server".
2

Add the Weblate MCP

Cursor will create or open .cursor/mcp.json in your project root. Paste the JSON snippet on the right. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Enable Agent mode

Open Composer (Cmd+I / Ctrl+I) and switch to Agent mode using the dropdown at the top. MCP tools are only available in Agent mode.
4

Verify the connection

Ask Cursor something like "List my recent Weblate transactions." If the MCP tools are loaded correctly, Cursor will call the Weblate tools automatically. You can also check Settings → MCP for a green status indicator.

.cursor/mcp.json

{
  "mcpServers": {
    "weblate-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

Get your connection token →

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 Cursor

You write code that calls `get_project_repository`. The AI client executes the tool and returns the live VCS output, which you can then immediately process or display in your editor’s context.

Yes. You'll use `create_user` and `add_group_roles` to write functions that manage user lifecycles, ensuring all necessary parameters are passed directly into your code.

Call `list_project_languages`. The resulting JSON data—showing usage counts and progress—is then available for you to consume directly within your function’s logic.

It does. You can chain calls, like first listing all projects with `list_projects`, and then iterating over that list using a subsequent tool call to get details for each one.

This server manages user roles, project structures, language definitions, component lists, and VCS operation logs within your Weblate instance.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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