How to Use the Localazy (AI Translation & Localization API) MCP in OpenAI Agents SDK

Q: How does Localazy (AI Translation & Localization API) connect to the OpenAI Agents SDK?

Install openai-agents and configure MCPServerStreamableHttp pointing to the Vinkius endpoint. Pass the server instance inside the mcpservers list when initializing your agent.

Q: Can my agent download translated files using Localazy (AI Translation & Localization API) and OpenAI Agents SDK?

Yes, your agent uses downloadfile to fetch the raw translated content. This allows the OpenAI Agents SDK to pull down completed translations during a build step.

Q: How do I speed up tool discovery for Localazy (AI Translation & Localization API) in OpenAI Agents SDK?

Set cacheToolsList=True in your connection parameters. This stops the SDK from querying the MCP Server on every single turn, keeping response times low.

Q: Can I control key priority in bulk?

Yes, the agent calls setkeypriority to flag important strings. This ensures your translators work on high-value user interface text before tackling minor strings.

Ship localized software faster by letting OpenAI Agents SDK handle translations, glossary terms, and files directly.

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Connect Localazy (AI Translation & Localization API) MCP to OpenAI Agents SDK

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Setup Localazy (AI Translation & Localization API) with OpenAI Agents SDK

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Sync source files directly from code

`import_content` uploads your raw localization files directly to your projects. Your agent reads local files and sends them to the API without manual export steps. You can verify what got uploaded by calling `list_files` to check the current file list. This keeps your translation platform perfectly in sync with your local git repository.

Send visual context using this MCP Server

`upload_screenshot` attaches Base64 encoded images directly to specific translation keys to give translators visual context. This prevents bad translations caused by lack of layout awareness. Agents update metadata using `update_screenshot` to link specific phrases or delete bad images using `delete_screenshot`. Better context means fewer back-and-forth questions from your localization team.

Maintain a strict translation glossary

`create_glossary_term` adds brand terms and technical jargon to your localization glossary to prevent incorrect machine translations. This enforces consistency across all target languages. Your agent updates existing terms with `update_glossary_term` or cleans up old terms using `delete_glossary_term`. This ensures your brand voice remains consistent across every language.

Setup guide

Set up Localazy (AI Translation & Localization API) MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Localazy (AI Translation & Localization API) tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Localazy (AI Translation & Localization API) tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Localazy (AI Translation & Localization API) tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="Localazy (AI Translation & Localization API) Agent",
            instructions="You have access to Localazy (AI Translation & Localization API) tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about Localazy (AI Translation & Localization API) MCP in OpenAI Agents SDK

Install `openai-agents` and configure `MCPServerStreamableHttp` pointing to the Vinkius endpoint. Pass the server instance inside the `mcp_servers` list when initializing your agent.

Yes, your agent uses `download_file` to fetch the raw translated content. This allows the OpenAI Agents SDK to pull down completed translations during a build step.

Set `cacheToolsList=True` in your connection parameters. This stops the SDK from querying the MCP Server on every single turn, keeping response times low.

Yes, the agent calls `set_key_priority` to flag important strings. This ensures your translators work on high-value user interface text before tackling minor strings.

Vinkius runs this MCP Server inside a secure, ephemeral V8 Isolate sandbox. Your translation keys, source files, and glossary terms only pass through to the API via encrypted HTTPS, and no data is stored permanently on the host.

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