How to Use the Crowdin MCP in OpenAI Agents SDK

Q: Can the OpenAI Agents SDK fetch Crowdin reports?

Yes. Use the listprojectreports tool to pull translation costs and progress metrics directly into your agent's memory.

Directly manage your Crowdin localization workflow inside the OpenAI Agents SDK with production-ready guardrails.

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Connect Crowdin MCP to OpenAI Agents SDK

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

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Full Crowdin project visibility for OpenAI Agents SDK

Your agent pulls real-time project data using `list_projects` and `get_project_details`. It sees current source and target language settings without leaving your Python codebase. Everything happens through your agent's execution loop. You get an immediate summary of project activity, letting your code react to translation status changes as they occur.

Automated file and task tracking

Monitor your translation pipeline by calling `list_project_files` and `list_project_tasks`. Your agent identifies which files need attention and tracks individual linguist assignments. This keeps your deployment synced with the actual state of your localization assets. You'll know exactly what's waiting for proofreading or translation at any moment.

Contextual asset management for localization

Retrieve vital translation metadata using `list_glossaries` and `list_translation_memories`. Your agent accesses these repositories to ensure terminology consistency across your entire project. Use `list_project_screenshots` to grab visual context for specific strings. Your OpenAI Agents SDK setup ensures these assets are always available when your agent needs to resolve ambiguity.

Setup guide

Set up Crowdin 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 Crowdin tools at runtime.
3

Create your Agent

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

Run the agent

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

asyncio.run(main())

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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 Crowdin. 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 Crowdin MCP in OpenAI Agents SDK

Install the server via your agent configuration. Pass the endpoint to the agent constructor, and the SDK automatically discovers every available tool.

Yes. Use the `list_project_reports` tool to pull translation costs and progress metrics directly into your agent's memory.

Absolutely. Since the agent validates every action through your defined constraints, any tool call to this MCP server is checked before it executes.

We only touch your project metadata, file paths, and translation status markers. Your actual source strings and translation content stay within your secure environment.

The server provides clean, structured responses. If you need strict schemas, verify the output against your own local Pydantic models before processing.

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