How to Use the Lokalise MCP in OpenAI Agents SDK

Q: Can my OpenAI Agents SDK setup handle translation orders automatically?

Yes, your agent can call listorders to check on external translation jobs. Since OpenAI Agents SDK supports tracing, you can monitor exactly when the agent checks these orders and logs status updates.

Q: How do guardrails protect my Lokalise keys in OpenAI Agents SDK?

You write validation hooks that intercept calls to updatekey or createkey. If the agent attempts to modify a protected namespace, the SDK blocks the tool execution before the API call is dispatched.

Q: How does the agent know which projects to target?

The agent calls listprojects to get a list of active translation projects under your account. It then uses getproject to inspect the targeted project's settings before initiating any file uploads.

Deploy production-grade OpenAI Agents SDK systems that manage your translation pipeline directly through the Lokalise API.

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Connect Lokalise MCP to OpenAI Agents SDK

Create your Vinkius account to connect Lokalise to OpenAI Agents SDK 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 Lokalise with OpenAI Agents SDK

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Automated File Syncing

The `upload_file` tool sends your localization files directly to your translation projects. Your OpenAI Agents SDK setup triggers this during CI/CD to prevent manual file shuffling. Once translations are ready, the agent calls `download_file` to pull the updated bundles. The OpenAI dashboard traces these calls, giving you full visibility into every file exchange without writing custom API polling code.

Safe key updates via this MCP Server

This MCP Server exposes `create_key` and `update_key` to let your agent structure translation targets on the fly. You set guardrails within OpenAI Agents SDK to prevent the agent from modifying critical legacy keys. Before execution, the agent uses `list_keys` to verify existing structures. If a key name violates your naming convention, the SDK's built-in validation halts the run before any bad data hits your Lokalise project.

Multi-Agent Translation Handoffs

The `add_translation` tool allows specialized agents to write localized content for specific target languages. You configure a coordinator agent that routes different locales to dedicated sub-agents. The coordinator uses `list_languages` to identify active locales, then hands off the task. Each sub-agent focuses on its assigned language, updating the project while OpenAI's tracing tracks which agent modified which string.

Setup guide

Set up Lokalise 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 Lokalise tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Lokalise tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Lokalise 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="Lokalise Agent",
            instructions="You have access to Lokalise 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 Lokalise MCP in OpenAI Agents SDK

Install the SDK and use the MCPServerStreamableHttp class pointing to the Vinkius endpoint. Pass this server instance inside the mcp_servers list when initializing your Agent. Set cacheToolsList=True to keep tool discovery fast and efficient.

Yes, your agent can call list_orders to check on external translation jobs. Since OpenAI Agents SDK supports tracing, you can monitor exactly when the agent checks these orders and logs status updates.

You write validation hooks that intercept calls to update_key or create_key. If the agent attempts to modify a protected namespace, the SDK blocks the tool execution before the API call is dispatched.

The agent calls list_projects to get a list of active translation projects under your account. It then uses get_project to inspect the targeted project's settings before initiating any file uploads.

This MCP Server accesses your translation keys, localization files, and API tokens. Vinkius runs the server in an ephemeral V8 sandbox, meaning your credentials are never written to persistent storage and are scrubbed immediately after the API call completes.

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