How to Use the Weblate MCP in LlamaIndex

Q: How can I check all available projects using Weblate and LlamaIndex?

You use listprojects. This gives you an indexed list of every localization project. Your agent can then query these results to build a knowledge base about your company's product portfolio.

Q: Can I get the file URL for all translations in one place using Weblate and LlamaIndex?

Yes, call getprojectfileurl. This provides the direct link to download all localized strings as a ZIP archive. Storing this URL in your knowledge base makes it easily retrievable later.

Q: What role details can LlamaIndex pull from Weblate?

The getrole tool pulls detailed information, including specific permission codenames associated with a given role. This data is excellent for indexing security policies.

Q: How do I manage group members using Weblate and LlamaIndex?

You can use listgroups to see existing groups, and then getgroup to retrieve their current roles, projects, and components. This lets your agent build a knowledge graph of team structure.

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Connect Weblate MCP to LlamaIndex

Create your Vinkius account to connect Weblate to LlamaIndex 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 LlamaIndex

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Deep dive into user activity.

If you want to query past work, run `get_user_contributions`. This tool lists translations and associated metadata that were contributed by a specific user. The output becomes indexed data for semantic search. You can also get summarized stats on an individual with `get_user_statistics`, which gives key performance indicators (KPIs) grounded in actual API numbers, not guesses.

Manage and read language definitions.

When setting up a new locale, use `create_language` to define the necessary rules. You can then check existing details using `get_language`, which returns specific data like plural formulas or aliases. Need global context? Run `list_languages` to get an indexed list of every language available in your Weblate setup.

Get detailed project and role information.

The tool `get_project` pulls all the details for a specific localization initiative. It's perfect for creating documents that reference live status data. You can also pull role specifics using `get_role`, which gives you permission codenames. Want to see what components belong to a project? Use `list_project_components`. This allows your RAG application to build a knowledge base around the physical structure of your translations.

Setup guide

Set up Weblate MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Weblate MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Weblate tools.",
)
response = await agent.run("List recent Weblate data")

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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 LlamaIndex

You use `list_projects`. This gives you an indexed list of every localization project. Your agent can then query these results to build a knowledge base about your company's product portfolio.

Yes, call `get_project_file_url`. This provides the direct link to download all localized strings as a ZIP archive. Storing this URL in your knowledge base makes it easily retrievable later.

The `get_role` tool pulls detailed information, including specific permission codenames associated with a given role. This data is excellent for indexing security policies.

You can use `list_groups` to see existing groups, and then `get_group` to retrieve their current roles, projects, and components. This lets your agent build a knowledge graph of team structure.

This server handles organizational settings like group memberships and user permissions. It specifically deals with structured metadata such as group roles, project assignments, and user administrative rights.

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