How to Use the Weblate MCP in LangChain

Q: How do I list all projects using Weblate and LangChain?

You just call listprojects. It returns a list of every project defined in your Weblate instance. This is the first step whenever you're trying to map out which localization efforts are active.

Q: What can I do with user notifications using Weblate and LangChain?

You use listusernotifications to see what a specific user is subscribed to. The manageusernotifications tool lets your agent change those settings, so the right people get alerted when their work is needed.

Q: Can LangChain check overall VCS status for a project?

Yep. Call getprojectrepository. This tells you the latest version control status—like whether it's clean, if there are commits pending, or if a pull needs to happen before proceeding.

Q: How do I find out what languages exist in a specific project using Weblate and LangChain?

Use listprojectlanguages. This tool gives you paginated statistics on every language defined within a single, given project. It's much more focused than listing all global languages.

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Connect Weblate MCP to LangChain

Create your Vinkius account to connect Weblate to LangChain 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 LangChain

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Manage Weblate users directly.

Need to onboard a team? Use `create_user` to build accounts and `update_user` to adjust permissions. You can also delete inactive accounts with `delete_user`. This lets your AI client manage the full lifecycle of people working on translations. It's perfect for setting up governance. After creating users, you'll want to use `add_group_admins` and `add_group_roles` to make sure everyone has exactly the right access level across various projects.

Control project structures.

When a new product launches, you need a place for translations. Start by calling `create_project`, then use `create_project_component` to define specific parts of the UI. You can also list existing components with `list_project_components` to ensure nothing was missed. If you need to adjust permissions later, you'll grab a role using `create_role`. Then, assign that role to a group via `add_group_roles`, ensuring the entire team works within defined boundaries.

Track translation progress and stats.

To see who did what, run `get_user_contributions` to list specific translations tied to a user. For overall performance metrics, use `list_project_languages` which gives paginated statistics for all language pairs in one project. Want global data? The `get_language_statistics` tool provides high-level numbers on how many strings are translated across an entire language definition. This is key for knowing where your localization efforts need the most focus.

Setup guide

Set up Weblate MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes Weblate tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "weblate-mcp": {
        "transport": "http",
        "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    }
}) as client:
    tools = client.get_tools()

    agent = create_react_agent(
        ChatOpenAI(model="gpt-4o"),
        tools,
    )
    result = await agent.ainvoke({
        "messages": "List recent Weblate transactions"
    })
    print(result["messages"][-1].content)

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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 LangChain

You just call `list_projects`. It returns a list of every project defined in your Weblate instance. This is the first step whenever you're trying to map out which localization efforts are active.

You use `list_user_notifications` to see what a specific user is subscribed to. The `manage_user_notifications` tool lets your agent change those settings, so the right people get alerted when their work is needed.

Yep. Call `get_project_repository`. This tells you the latest version control status—like whether it's clean, if there are commits pending, or if a pull needs to happen before proceeding.

Use `list_project_languages`. This tool gives you paginated statistics on every language defined within a single, given project. It's much more focused than listing all global languages.

This server handles user account information and contribution records. Specifically, it deals with structured user metadata like names, email addresses, roles, and project contributions.

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