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How to Use the Transifex MCP in OpenAI Agents SDK

Build reliable localization pipelines with the OpenAI Agents SDK.

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OpenAI Agents SDK

Connect Transifex MCP to OpenAI Agents SDK

Create your Vinkius account to connect Transifex 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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Discovering Transifex Projects via MCP Server

The agent can list all organizations you belong to using `list_organizations`. From there, it runs `list_projects`, optionally filtering the results by a specific organization ID. This gives your AI client a map of every project available in Transifex.

Targeting Specific Localization Resources

Need to find a particular piece of content? Your agent can narrow down the search using `get_resource`, which requires an organization, project, and resource slug. It also offers `list_resources` if you want to see all available resources within a whole project.

Listing Source Strings for Review

When the agent finds the right resource ID, it runs `list_resource_strings`. This action shows the original source strings—the content that needs localization. If you only need one string, `get_resource_string` handles that lookup.

Setup guide

Set up Transifex 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. 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. 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 Transifex tools at runtime.

  3. 3

    Create your Agent

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

  4. 4

    Run the agent

    Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Transifex 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="Transifex Agent",
            instructions="You have access to Transifex tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Transifex. 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 Transifex MCP in OpenAI Agents SDK

You just call `list_languages`. This tool provides a full list of supported language codes, letting your agent know what locales are available for translation.
Yes. The agent runs `list_organizations` first, and then it calls `list_projects`. This sequence of actions ensures it finds every project you have access to within your account.
Absolutely. You can use `get_resource` to pinpoint an exact resource using its unique slug identifiers for organization, project, and resource scope.
This server handles metadata about localization assets—specifically language codes (e.g., `en`, `pt_BR`), organization slugs, project slugs, and resource strings.
The agent uses the simple `get_language` function. It only requires you to pass the desired ID (like 'en') and immediately returns the details.

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