How to integrate Crowdin MCP with OpenAI Agents SDK

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Introduction

This guide walks you through connecting Crowdin to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Crowdin agent that can create a new crowdin project for our app, add new source file to the translations project, assign sprint label to specific string ids, delete obsolete translation branch from project through natural language commands.

This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Crowdin account through Composio's Crowdin MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the necessary dependencies
  • Initialize Composio and create a Tool Router session for Crowdin
  • Configure an AI agent that can use Crowdin as a tool
  • Run a live chat session where you can ask the agent to perform Crowdin operations

What is open-ai-agents-sdk?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.

Key features include:

  • Hosted MCP Tools: Connect to external services through hosted MCP endpoints
  • SQLite Sessions: Persist conversation history across interactions
  • Simple API: Clean interface with Agent, Runner, and tool configuration
  • Streaming Support: Real-time response streaming for interactive applications

What is the Crowdin MCP server, and what's possible with it?

The Crowdin MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Crowdin account. It provides structured and secure access to your localization projects, so your agent can manage branches, organize files, label content, automate webhooks, and orchestrate translation workflows on your behalf.

  • Branch and project management: Easily have your agent create, delete, or organize Crowdin projects and branches to streamline new releases or features.
  • Dynamic file handling: Let your agent add new files to projects, ensuring your translation assets are always up to date and properly organized by branch or directory.
  • Labeling and content categorization: Direct your agent to create, assign, or remove labels on resources and strings, helping you segment and track translation tasks with precision.
  • Workflow automation with webhooks: Automate your translation process by having the agent set up or remove webhooks for real-time notifications and integrations.
  • Resource cleanup and maintenance: Empower your agent to delete obsolete branches, labels, webhooks, or entire projects, keeping your Crowdin workspace clean and focused.

Supported Tools & Triggers

Tools
Add BranchTool to create a new branch in a crowdin project.
Add FileTool to add a new file to a crowdin project.
Add LabelTool to create a new label in a crowdin project.
Create Crowdin ProjectTool to create a new project in crowdin.
Add WebhookTool to create a new webhook in a crowdin project.
Assign Label to StringsTool to assign the specified label to provided string ids in a project.
Delete BranchTool to delete a specific branch from a crowdin project.
Delete LabelTool to delete the label identified by the specified label id in a project.
Delete ProjectTool to delete a crowdin project by its id.
Delete WebhookTool to delete the webhook identified by the specified webhook id in a crowdin project.
Edit FileTool to update file details in a project.
Edit LabelTool to edit a label in a crowdin project.
Edit ProjectTool to update project details using json-patch.
Edit StringTool to update string details in a crowdin project.
Get LabelTool to retrieve information about the label identified by the specified label id in a project.
Get LanguageTool to retrieve details of a specific language.
Get Member InfoTool to retrieve information about a project member.
Get ProjectTool to retrieve details of a specific crowdin project.
Get StringTool to retrieve details of a specific string in a crowdin project.
Get WebhookTool to retrieve information about the webhook identified by the specified webhook id in a project.
List BranchesTool to list all branches in a crowdin project.
List FilesTool to list files in a crowdin project.
List LabelsTool to list labels in a crowdin project.
List LanguagesTool to retrieve a list of supported languages.
List Project MembersTool to list members in a crowdin project.
List ProjectsTool to retrieve a list of all crowdin projects with optional filters.
List ReportsTool to list reports for a given crowdin project.
Upload StorageTool to upload a file to crowdin storage.

What is the Composio tool router, and how does it fit here?

What is Tool Router?

Composio's Tool Router helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Prerequisites

Before starting, make sure you have:
  • Composio API Key and OpenAI API Key
  • Primary know-how of OpenAI Agents SDK
  • A live Crowdin project
  • Some knowledge of Python or Typescript

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key

Install dependencies

pip install composio_openai_agents openai-agents python-dotenv

Install the Composio SDK and the OpenAI Agents SDK.

Set up environment variables

bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com

Create a .env file and add your OpenAI and Composio API keys.

Import dependencies

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
What's happening:
  • You're importing all necessary libraries.
  • The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Crowdin.

Set up the Composio instance

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
What's happening:
  • load_dotenv() loads your .env file so OPENAI_API_KEY and COMPOSIO_API_KEY are available as environment variables.
  • Creating a Composio instance using the API Key and OpenAIAgentsProvider class.

Create a Tool Router session

# Create a Crowdin Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["crowdin"]
)

mcp_url = session.mcp.url

What is happening:

  • You give the Tool Router the user id and the toolkits you want available. Here, it is only crowdin.
  • The router checks the user's Crowdin connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Crowdin.
  • This approach keeps things lightweight and lets the agent request Crowdin tools only when needed during the conversation.

Configure the agent

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Crowdin. "
        "Help users perform Crowdin operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)
What's happening:
  • We're creating an Agent instance with a name, model (gpt-5), and clear instructions about its purpose.
  • The agent's instructions tell it that it can access Crowdin and help with queries, inserts, updates, authentication, and fetching database information.
  • The tools array includes a HostedMCPTool that connects to the MCP server URL we created earlier.
  • The headers dict includes the Composio API key for secure authentication with the MCP server.
  • require_approval: 'never' means the agent can execute Crowdin operations without asking for permission each time, making interactions smoother.

Start chat loop and handle conversation

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
What's happening:
  • The program prints a session URL that you visit to authorize Crowdin.
  • After authorization, the chat begins.
  • Each message you type is processed by the agent using Runner.run().
  • The responses are printed to the console, and conversations are saved locally using SQLite.
  • Typing exit, quit, or q cleanly ends the chat.

Complete Code

Here's the complete code to get you started with Crowdin and open-ai-agents-sdk:

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["crowdin"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Crowdin. "
        "Help users perform Crowdin operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())

Conclusion

This was a starter code for integrating Crowdin MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Crowdin.

Key features:

  • Hosted MCP tool integration through Composio's Tool Router
  • SQLite session persistence for conversation history
  • Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

How to build Crowdin MCP Agent with another framework

Claude Agent SDK

Claude Agent SDK

Use Crowdin MCP with Claude Agent SDK

Google ADK

Google ADK

Use Crowdin MCP with Google ADK

LangChain

LangChain

Use Crowdin MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Crowdin MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Crowdin MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Crowdin MCP with LlamaIndex

CrewAI

CrewAI

Use Crowdin MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Crowdin MCP?

With a standalone Crowdin MCP server, the agents and LLMs can only access a fixed set of Crowdin tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Crowdin and many other apps based on the task at hand, all through a single MCP endpoint.

Can I use Tool Router MCP with OpenAI Agents SDK?

Yes, you can. OpenAI Agents SDK fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Crowdin tools.

Can I manage the permissions and scopes for Crowdin while using Tool Router?

Yes, absolutely. You can configure which Crowdin scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Crowdin data and credentials are handled as safely as possible.

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