# How to integrate Crowdin MCP with Vercel AI SDK v6 ```json { "title": "How to integrate Crowdin MCP with Vercel AI SDK v6", "toolkit": "Crowdin", "toolkit_slug": "crowdin", "framework": "Vercel AI SDK", "framework_slug": "ai-sdk", "url": "https://composio.dev/toolkits/crowdin/framework/ai-sdk", "markdown_url": "https://composio.dev/toolkits/crowdin/framework/ai-sdk.md", "updated_at": "2026-05-06T08:07:38.198Z" } ``` ## Introduction This guide walks you through connecting Crowdin to Vercel AI SDK v6 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 through natural language commands. This guide will help you understand how to give your Vercel AI 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. ## Also integrate Crowdin with - [OpenAI Agents SDK](https://composio.dev/toolkits/crowdin/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/crowdin/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/crowdin/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/crowdin/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/crowdin/framework/codex) - [OpenClaw](https://composio.dev/toolkits/crowdin/framework/openclaw) - [Hermes](https://composio.dev/toolkits/crowdin/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/crowdin/framework/cli) - [Google ADK](https://composio.dev/toolkits/crowdin/framework/google-adk) - [LangChain](https://composio.dev/toolkits/crowdin/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/crowdin/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/crowdin/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/crowdin/framework/crew-ai) ## TL;DR Here's what you'll learn: - How to set up and configure a Vercel AI SDK agent with Crowdin integration - Using Composio's Tool Router to dynamically load and access Crowdin tools - Creating an MCP client connection using HTTP transport - Building an interactive CLI chat interface with conversation history management - Handling tool calls and results within the Vercel AI SDK framework ## What is Vercel AI SDK? The Vercel AI SDK is a TypeScript library for building AI-powered applications. It provides tools for creating agents that can use external services and maintain conversation state. Key features include: - streamText: Core function for streaming responses with real-time tool support - MCP Client: Built-in support for Model Context Protocol via @ai-sdk/mcp - Step Counting: Control multi-step tool execution with stopWhen: stepCountIs() - OpenAI Provider: Native integration with OpenAI models ## 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 | Tool slug | Name | Description | |---|---|---| | `CROWDIN_ADD_BRANCH` | Add Branch | Tool to create a new branch in a crowdin project. use when you need to isolate translations for a new feature or release. | | `CROWDIN_ADD_FILE` | Add File | Tool to add a new file to a crowdin project. use after uploading the file to storage to place it under the specified project, branch, or directory. | | `CROWDIN_ADD_LABEL` | Add Label | Tool to create a new label in a crowdin project. use when you need to tag resources with a custom identifier, such as 'sprint-5'. | | `CROWDIN_ADD_PROJECT` | Create Crowdin Project | Tool to create a new project in crowdin. use before uploading source files to initialize translation workflows. | | `CROWDIN_ADD_WEBHOOK` | Add Webhook | Tool to create a new webhook in a crowdin project. use after confirming the project id and desired event triggers. | | `CROWDIN_ASSIGN_LABEL_TO_STRINGS` | Assign Label to Strings | Tool to assign the specified label to provided string ids in a project. use after creating the label or verifying string ids to categorize content. | | `CROWDIN_DELETE_BRANCH` | Delete Branch | Tool to delete a specific branch from a crowdin project. use when you need to remove an obsolete branch after it's fully merged. | | `CROWDIN_DELETE_LABEL` | Delete Label | Tool to delete the label identified by the specified label id in a project. use when you need to remove outdated or incorrect labels. ensure no resources reference the label before deletion. | | `CROWDIN_DELETE_PROJECT` | Delete Project | Tool to delete a crowdin project by its id. use when you need to permanently remove a project after confirming no further usage. ensure all resources are no longer needed before deletion. | | `CROWDIN_DELETE_WEBHOOK` | Delete Webhook | Tool to delete the webhook identified by the specified webhook id in a crowdin project. use when you need to remove obsolete or incorrect webhooks after confirming project and webhook ids. | | `CROWDIN_EDIT_FILE` | Edit File | Tool to update file details in a project. use after confirming valid project and file ids. | | `CROWDIN_EDIT_LABEL` | Edit Label | Tool to edit a label in a crowdin project. use when you need to update the name or description of an existing label. ensure the label exists before using. example: edit label 42 to 'release-1.1'. | | `CROWDIN_EDIT_PROJECT` | Edit Project | Tool to update project details using json-patch. use after confirming project settings to modify metadata like name, description, visibility, or languages. | | `CROWDIN_EDIT_STRING` | Edit String | Tool to update string details in a crowdin project. use when you need to modify a string's text or metadata after creation. | | `CROWDIN_GET_LABEL` | Get Label | Tool to retrieve information about the label identified by the specified label id in a project. use after confirming the project context to fetch label details. | | `CROWDIN_GET_LANGUAGE` | Get Language | Tool to retrieve details of a specific language. use when you have a language identifier and need locale codes and plural rules before configuring translations. | | `CROWDIN_GET_MEMBER_INFO` | Get Member Info | Tool to retrieve information about a project member. use when you need to inspect details for a specific user within a project after obtaining their member id. | | `CROWDIN_GET_PROJECT` | Get Project | Tool to retrieve details of a specific crowdin project. use when you need to inspect project settings before making updates. | | `CROWDIN_GET_STRING` | Get String | Tool to retrieve details of a specific string in a crowdin project. use after confirming the project and string ids to fetch its metadata. | | `CROWDIN_GET_WEBHOOK` | Get Webhook | Tool to retrieve information about the webhook identified by the specified webhook id in a project. use after confirming the project context to fetch webhook details. | | `CROWDIN_LIST_BRANCHES` | List Branches | Tool to list all branches in a crowdin project. use after selecting a project to view its branch structure. supports pagination and optional filtering by branch id. | | `CROWDIN_LIST_FILES` | List Files | Tool to list files in a crowdin project. use when you need to retrieve a list of project files with optional filters by directory, group, or branch before processing. | | `CROWDIN_LIST_LABELS` | List Labels | Tool to list labels in a crowdin project. use when you need to retrieve all labels for a specific project with optional pagination. | | `CROWDIN_LIST_LANGUAGES` | List Languages | Tool to retrieve a list of supported languages. use when you need to fetch all languages crowdin supports before starting localization. | | `CROWDIN_LIST_PROJECT_MEMBERS` | List Project Members | Tool to list members in a crowdin project. use when you need to retrieve project member list for management tasks after confirming the project id. | | `CROWDIN_LIST_PROJECTS` | List Projects | Tool to retrieve a list of all crowdin projects with optional filters. use when you need to paginate through or filter projects by owner, group, language inclusion, or archive status. | | `CROWDIN_LIST_REPORTS` | List Reports | Tool to list reports for a given crowdin project. use after confirming project id to retrieve available reports. supports pagination via limit and offset. | | `CROWDIN_UPLOAD_STORAGE` | Upload Storage | Tool to upload a file to crowdin storage. use when you need to obtain a storageid for further operations like adding files to a project. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Crowdin MCP server is an implementation of the Model Context Protocol that connects your AI agent to Crowdin. It provides structured and secure access so your agent can perform Crowdin operations on your behalf through a secure, permission-based interface. With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster. ## Step-by-step Guide ### 1. Prerequisites Before you begin, make sure you have: - Node.js and npm installed - A Composio account with API key - An OpenAI API key ### 1. Getting API Keys for OpenAI and Composio OpenAI API Key - Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) 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 - Log in to the [Composio dashboard](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs). - Navigate to your API settings and generate a new API key. - Store this key securely as you'll need it for authentication. ### 2. Install required dependencies First, install the necessary packages for your project. What you're installing: - @ai-sdk/openai: Vercel AI SDK's OpenAI provider - @ai-sdk/mcp: MCP client for Vercel AI SDK - @composio/core: Composio SDK for tool integration - ai: Core Vercel AI SDK - dotenv: Environment variable management ```bash npm install @ai-sdk/openai @ai-sdk/mcp @composio/core ai dotenv ``` ### 3. Set up environment variables Create a .env file in your project root. What's needed: - OPENAI_API_KEY: Your OpenAI API key for GPT model access - COMPOSIO_API_KEY: Your Composio API key for tool access - COMPOSIO_USER_ID: A unique identifier for the user session ```bash OPENAI_API_KEY=your_openai_api_key_here COMPOSIO_API_KEY=your_composio_api_key_here COMPOSIO_USER_ID=your_user_id_here ``` ### 4. Import required modules and validate environment What's happening: - We're importing all necessary libraries including Vercel AI SDK's OpenAI provider and Composio - The dotenv/config import automatically loads environment variables - The MCP client import enables connection to Composio's tool server ```typescript import "dotenv/config"; import { openai } from "@ai-sdk/openai"; import { Composio } from "@composio/core"; import * as readline from "readline"; import { streamText, type ModelMessage, stepCountIs } from "ai"; import { createMCPClient } from "@ai-sdk/mcp"; const composioAPIKey = process.env.COMPOSIO_API_KEY; const composioUserID = process.env.COMPOSIO_USER_ID; if (!process.env.OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set"); if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set"); if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set"); const composio = new Composio({ apiKey: composioAPIKey, }); ``` ### 5. Create Tool Router session and initialize MCP client What's happening: - We're creating a Tool Router session that gives your agent access to Crowdin tools - The create method takes the user ID and specifies which toolkits should be available - The returned mcp object contains the URL and authentication headers needed to connect to the MCP server - This session provides access to all Crowdin-related tools through the MCP protocol ```typescript async function main() { // Create a tool router session for the user const session = await composio.create(composioUserID!, { toolkits: ["crowdin"], }); const mcpUrl = session.mcp.url; ``` ### 6. Connect to MCP server and retrieve tools What's happening: - We're creating an MCP client that connects to our Composio Tool Router session via HTTP - The mcp.url provides the endpoint, and mcp.headers contains authentication credentials - The type: "http" is important - Composio requires HTTP transport - tools() retrieves all available Crowdin tools that the agent can use ```typescript const mcpClient = await createMCPClient({ transport: { type: "http", url: mcpUrl, headers: session.mcp.headers, // Authentication headers for the Composio MCP server }, }); const tools = await mcpClient.tools(); ``` ### 7. Initialize conversation and CLI interface What's happening: - We initialize an empty messages array to maintain conversation history - A readline interface is created to accept user input from the command line - Instructions are displayed to guide the user on how to interact with the agent ```typescript let messages: ModelMessage[] = []; console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n"); console.log( "Ask any questions related to crowdin, like summarize my last 5 emails, send an email, etc... :)))\n", ); const rl = readline.createInterface({ input: process.stdin, output: process.stdout, prompt: "> ", }); rl.prompt(); ``` ### 8. Handle user input and stream responses with real-time tool feedback What's happening: - We use streamText instead of generateText to stream responses in real-time - toolChoice: "auto" allows the model to decide when to use Crowdin tools - stopWhen: stepCountIs(10) allows up to 10 steps for complex multi-tool operations - onStepFinish callback displays which tools are being used in real-time - We iterate through the text stream to create a typewriter effect as the agent responds - The complete response is added to conversation history to maintain context - Errors are caught and displayed with helpful retry suggestions ```typescript rl.on("line", async (userInput: string) => { const trimmedInput = userInput.trim(); if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) { console.log("\nGoodbye!"); rl.close(); process.exit(0); } if (!trimmedInput) { rl.prompt(); return; } messages.push({ role: "user", content: trimmedInput }); console.log("\nAgent is thinking...\n"); try { const stream = streamText({ model: openai("gpt-5"), messages, tools, toolChoice: "auto", stopWhen: stepCountIs(10), onStepFinish: (step) => { for (const toolCall of step.toolCalls) { console.log(`[Using tool: ${toolCall.toolName}]`); } if (step.toolCalls.length > 0) { console.log(""); // Add space after tool calls } }, }); for await (const chunk of stream.textStream) { process.stdout.write(chunk); } console.log("\n\n---\n"); // Get final result for message history const response = await stream.response; if (response?.messages?.length) { messages.push(...response.messages); } } catch (error) { console.error("\nAn error occurred while talking to the agent:"); console.error(error); console.log( "\nYou can try again or restart the app if it keeps happening.\n", ); } finally { rl.prompt(); } }); rl.on("close", async () => { await mcpClient.close(); console.log("\n๐Ÿ‘‹ Session ended."); process.exit(0); }); } main().catch((err) => { console.error("Fatal error:", err); process.exit(1); }); ``` ## Complete Code ```typescript import "dotenv/config"; import { openai } from "@ai-sdk/openai"; import { Composio } from "@composio/core"; import * as readline from "readline"; import { streamText, type ModelMessage, stepCountIs } from "ai"; import { createMCPClient } from "@ai-sdk/mcp"; const composioAPIKey = process.env.COMPOSIO_API_KEY; const composioUserID = process.env.COMPOSIO_USER_ID; if (!process.env.OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set"); if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set"); if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set"); const composio = new Composio({ apiKey: composioAPIKey, }); async function main() { // Create a tool router session for the user const session = await composio.create(composioUserID!, { toolkits: ["crowdin"], }); const mcpUrl = session.mcp.url; const mcpClient = await createMCPClient({ transport: { type: "http", url: mcpUrl, headers: session.mcp.headers, // Authentication headers for the Composio MCP server }, }); const tools = await mcpClient.tools(); let messages: ModelMessage[] = []; console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n"); console.log( "Ask any questions related to crowdin, like summarize my last 5 emails, send an email, etc... :)))\n", ); const rl = readline.createInterface({ input: process.stdin, output: process.stdout, prompt: "> ", }); rl.prompt(); rl.on("line", async (userInput: string) => { const trimmedInput = userInput.trim(); if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) { console.log("\nGoodbye!"); rl.close(); process.exit(0); } if (!trimmedInput) { rl.prompt(); return; } messages.push({ role: "user", content: trimmedInput }); console.log("\nAgent is thinking...\n"); try { const stream = streamText({ model: openai("gpt-5"), messages, tools, toolChoice: "auto", stopWhen: stepCountIs(10), onStepFinish: (step) => { for (const toolCall of step.toolCalls) { console.log(`[Using tool: ${toolCall.toolName}]`); } if (step.toolCalls.length > 0) { console.log(""); // Add space after tool calls } }, }); for await (const chunk of stream.textStream) { process.stdout.write(chunk); } console.log("\n\n---\n"); // Get final result for message history const response = await stream.response; if (response?.messages?.length) { messages.push(...response.messages); } } catch (error) { console.error("\nAn error occurred while talking to the agent:"); console.error(error); console.log( "\nYou can try again or restart the app if it keeps happening.\n", ); } finally { rl.prompt(); } }); rl.on("close", async () => { await mcpClient.close(); console.log("\n๐Ÿ‘‹ Session ended."); process.exit(0); }); } main().catch((err) => { console.error("Fatal error:", err); process.exit(1); }); ``` ## Conclusion You've successfully built a Crowdin agent using the Vercel AI SDK with streaming capabilities! This implementation provides a powerful foundation for building AI applications with natural language interfaces and real-time feedback. Key features of this implementation: - Real-time streaming responses for a better user experience with typewriter effect - Live tool execution feedback showing which tools are being used as the agent works - Dynamic tool loading through Composio's Tool Router with secure authentication - Multi-step tool execution with configurable step limits (up to 10 steps) - Comprehensive error handling for robust agent execution - Conversation history maintenance for context-aware responses You can extend this further by adding custom error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows. ## How to build Crowdin MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/crowdin/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/crowdin/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/crowdin/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/crowdin/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/crowdin/framework/codex) - [OpenClaw](https://composio.dev/toolkits/crowdin/framework/openclaw) - [Hermes](https://composio.dev/toolkits/crowdin/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/crowdin/framework/cli) - [Google ADK](https://composio.dev/toolkits/crowdin/framework/google-adk) - [LangChain](https://composio.dev/toolkits/crowdin/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/crowdin/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/crowdin/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/crowdin/framework/crew-ai) ## Related Toolkits - [Apilio](https://composio.dev/toolkits/apilio) - Apilio is a home automation platform that lets you connect and control smart devices from different brands. It helps you build flexible automations with complex conditions, schedules, and integrations. - [Basin](https://composio.dev/toolkits/basin) - Basin is a no-code form backend for quickly setting up reliable contact forms. It lets you collect and manage form submissions without writing any server-side code. - [Bouncer](https://composio.dev/toolkits/bouncer) - Bouncer is an email validation platform that verifies the authenticity of email addresses in real-time and batch. It helps boost deliverability and reduce bounce rates for your communications. - [Conveyor](https://composio.dev/toolkits/conveyor) - Conveyor is a platform that automates security reviews with a Trust Center and AI-driven questionnaire automation. It streamlines compliance and vendor security processes for faster, hassle-free reviews. - [Databox](https://composio.dev/toolkits/databox) - Databox is a business analytics platform that connects your data from any tool and device. It helps you track KPIs, build dashboards, and discover actionable insights. - [Detrack](https://composio.dev/toolkits/detrack) - Detrack is a delivery management platform for real-time tracking and proof of delivery. It helps businesses automate notifications and keep customers updated every step of the way. - [Dnsfilter](https://composio.dev/toolkits/dnsfilter) - Dnsfilter is a cloud-based DNS security and content filtering solution. It helps organizations block online threats and manage safe internet access with ease. - [Faraday](https://composio.dev/toolkits/faraday) - Faraday lets you embed AI in workflows across your stack for smarter automation. It boosts your favorite tools with actionable intelligence and seamless integration. - [Feathery](https://composio.dev/toolkits/feathery) - Feathery is an AI-powered platform for building dynamic data intake forms with advanced logic. It helps teams automate complex workflows and collect structured data with ease. - [Fillout forms](https://composio.dev/toolkits/fillout_forms) - Fillout forms is an online platform for building and managing forms with a flexible API. It lets you create, distribute, and collect responses from forms with ease. - [Formdesk](https://composio.dev/toolkits/formdesk) - Formdesk is an online form builder for creating and managing professional forms. It's perfect for collecting data, automating workflows, and integrating form submissions with your favorite services. - [Formsite](https://composio.dev/toolkits/formsite) - Formsite lets you build online forms and surveys with drag-and-drop simplicity. Capture, manage, and integrate form responses securely for streamlined workflows. - [Graphhopper](https://composio.dev/toolkits/graphhopper) - GraphHopper is an enterprise-grade Directions API for routing, optimization, and geocoding across multiple vehicle types. It enables fast, reliable route planning and logistics automation for businesses. - [Hyperbrowser](https://composio.dev/toolkits/hyperbrowser) - Hyperbrowser is a next-generation platform for scalable browser automation. It empowers AI agents to interact with web apps, automate workflows, and handle browser sessions at scale. - [La Growth Machine](https://composio.dev/toolkits/lagrowthmachine) - La Growth Machine automates multi-channel sales outreach and routine tasks for sales teams. Streamline your workflow and focus on closing more deals. - [Leverly](https://composio.dev/toolkits/leverly) - Leverly is a workflow automation platform that connects and coordinates actions across your apps. It streamlines repetitive processes so your business runs smoother, faster, and with fewer manual steps. - [Maintainx](https://composio.dev/toolkits/maintainx) - Maintainx is a cloud-based CMMS for centralizing maintenance data, communication, and workflows. It helps organizations streamline maintenance operations and improve team coordination. - [Make](https://composio.dev/toolkits/make) - Make is an automation platform that connects your favorite apps and services. Build powerful, custom workflows without writing code. - [Ntfy](https://composio.dev/toolkits/ntfy) - Ntfy is a notification service to send push messages to phones or desktops. Instantly deliver alerts and updates to users, devices, or teams. - [Persona](https://composio.dev/toolkits/persona) - Persona offers identity infrastructure to automate user verification and compliance. It helps organizations securely verify users and reduce fraud risk. ## Frequently Asked Questions ### 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 Vercel AI SDK v6? Yes, you can. Vercel AI SDK v6 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. --- [See all toolkits](https://composio.dev/toolkits) ยท [Composio docs](https://docs.composio.dev/llms.txt)