# How to integrate Tiktok MCP with Vercel AI SDK v6 ```json { "title": "How to integrate Tiktok MCP with Vercel AI SDK v6", "toolkit": "Tiktok", "toolkit_slug": "tiktok", "framework": "Vercel AI SDK", "framework_slug": "ai-sdk", "url": "https://composio.dev/toolkits/tiktok/framework/ai-sdk", "markdown_url": "https://composio.dev/toolkits/tiktok/framework/ai-sdk.md", "updated_at": "2026-05-12T10:28:29.420Z" } ``` ## Introduction This guide walks you through connecting Tiktok to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Tiktok agent that can upload a new video from your library, list your most recent tiktok videos, fetch your latest tiktok follower stats through natural language commands. This guide will help you understand how to give your Vercel AI SDK agent real control over a Tiktok account through Composio's Tiktok MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Tiktok with - [ChatGPT](https://composio.dev/toolkits/tiktok/framework/chatgpt) - [OpenAI Agents SDK](https://composio.dev/toolkits/tiktok/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/tiktok/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/tiktok/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/tiktok/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/tiktok/framework/codex) - [Cursor](https://composio.dev/toolkits/tiktok/framework/cursor) - [VS Code](https://composio.dev/toolkits/tiktok/framework/vscode) - [OpenCode](https://composio.dev/toolkits/tiktok/framework/opencode) - [OpenClaw](https://composio.dev/toolkits/tiktok/framework/openclaw) - [Hermes](https://composio.dev/toolkits/tiktok/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/tiktok/framework/cli) - [Google ADK](https://composio.dev/toolkits/tiktok/framework/google-adk) - [LangChain](https://composio.dev/toolkits/tiktok/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/tiktok/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/tiktok/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/tiktok/framework/crew-ai) ## TL;DR Here's what you'll learn: - How to set up and configure a Vercel AI SDK agent with Tiktok integration - Using Composio's Tool Router to dynamically load and access Tiktok 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 Tiktok MCP server, and what's possible with it? The Tiktok MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Tiktok account. It provides structured and secure access to your Tiktok profile and content, so your agent can fetch user analytics, manage your videos, post new content, and monitor publishing status—all on your behalf. - Automated video uploads and publishing: Let your agent upload single or multiple videos, then finalize and publish them to your Tiktok account seamlessly. - Profile insights and analytics: Fetch comprehensive user information and performance stats, giving you quick access to follower counts, engagement metrics, and more. - Content management: List all your videos or those of a specified creator, making it easy to organize, review, or reference your posted content. - Photo posting automation: Enable your agent to create and post photos directly through the Tiktok content posting API, streamlining your visual content workflow. - Real-time publish status monitoring: Check the current status of your video uploads or publishing process, so you’re always up to date on which content is live or pending. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `TIKTOK_FETCH_PUBLISH_STATUS` | Fetch publish status | Check the processing status of a TikTok video or photo post using its publish_id. Use this action to poll the status of content after initiating an upload or post. The API returns detailed information about processing stages (upload, download, moderation) and any errors that occurred. Non-terminal statuses mean processing is still pending — never re-initiate TIKTOK_PUBLISH_VIDEO for the same publish_id. Use exponential backoff when polling (e.g., 5s→10s→20s) to avoid the 30 requests/minute per access token rate limit. | | `TIKTOK_GET_ACTION_CATEGORIES` | Get action categories | Tool to retrieve available action categories from TikTok Marketing API. Use when you need to get the list of conversion event categories for creating or managing TikTok ad campaigns with conversion tracking. | | `TIKTOK_GET_TERM` | Get terms | Tool to retrieve terms from TikTok Business API. Use when you need to fetch advertiser or agency terms for a specific advertiser ID. | | `TIKTOK_GET_USER_STATS` | Get user stats | Fetches TikTok user information and statistics for the authenticated user. Retrieves user stats (follower_count, following_count, likes_count, video_count) and can optionally fetch profile fields (display_name, username, bio_description, etc.) and basic info (open_id, union_id, avatar URLs). Returns only the fields requested in the fields parameter. Only works for the authenticated account; cannot fetch arbitrary public profiles. Stats may be delayed and not reflect the most recent activity. | | `TIKTOK_LIST_GMV_MAX_OCCUPIED_CUSTOM_SHOP_ADS` | List GMV Max occupied custom shop ads | Tool to get GMV Max occupied custom shop ads list for a TikTok advertiser. Use this action when you need to retrieve information about which custom shop ads are currently occupied for GMV Max campaigns. This is part of the TikTok Business API and requires appropriate advertiser access. | | `TIKTOK_LIST_VIDEOS` | List videos | Lists videos for the authenticated user (or specified creator). Does not provide a global TikTok-wide feed. | | `TIKTOK_POST_PHOTO` | Post photo | Create a photo post (1-35 images) on TikTok via Content Posting API. Supports two modes: - MEDIA_UPLOAD: Uploads photos to user's inbox for review/editing before posting - DIRECT_POST: Immediately posts photos to user's TikTok account IMPORTANT: Photo URLs must be from your TikTok-verified domain. Unverified domains will return 403 Forbidden. Unaudited apps can only post with privacy='SELF_ONLY'. Rate limit: 6 requests per minute per user access token. Reference: https://developers.tiktok.com/doc/content-posting-api-reference-photo-post | | `TIKTOK_PUBLISH_VIDEO` | Publish video | Publishes a video to TikTok by pulling it from a public URL. TikTok downloads the video from the provided URL and publishes it directly to the creator's profile. Publishing is asynchronous — after calling this action, poll TIKTOK_FETCH_PUBLISH_STATUS with the returned publish_id to check completion. For uploading video files instead of URLs, use TIKTOK_UPLOAD_VIDEO. | | `TIKTOK_UPLOAD_VIDEO` | Upload video | Uploads a video to TikTok via the Content Posting API (init + single-part upload). This action initializes an upload session to obtain a presigned upload URL, then uploads the entire file with a single PUT request. Use a subsequent action to publish the post. Ensure the video file is fully generated and available before calling this action. | | `TIKTOK_UPLOAD_VIDEOS` | Upload videos (batch) | Uploads multiple videos to TikTok concurrently (init + single-part upload per file). | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Tiktok MCP server is an implementation of the Model Context Protocol that connects your AI agent to Tiktok. It provides structured and secure access so your agent can perform Tiktok 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 Tiktok 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 Tiktok-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: ["tiktok"], }); 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 Tiktok 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 tiktok, 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 Tiktok 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("\n👋 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: ["tiktok"], }); 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 tiktok, 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("\n👋 Session ended."); process.exit(0); }); } main().catch((err) => { console.error("Fatal error:", err); process.exit(1); }); ``` ## Conclusion You've successfully built a Tiktok 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 Tiktok MCP Agent with another framework - [ChatGPT](https://composio.dev/toolkits/tiktok/framework/chatgpt) - [OpenAI Agents SDK](https://composio.dev/toolkits/tiktok/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/tiktok/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/tiktok/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/tiktok/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/tiktok/framework/codex) - [Cursor](https://composio.dev/toolkits/tiktok/framework/cursor) - [VS Code](https://composio.dev/toolkits/tiktok/framework/vscode) - [OpenCode](https://composio.dev/toolkits/tiktok/framework/opencode) - [OpenClaw](https://composio.dev/toolkits/tiktok/framework/openclaw) - [Hermes](https://composio.dev/toolkits/tiktok/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/tiktok/framework/cli) - [Google ADK](https://composio.dev/toolkits/tiktok/framework/google-adk) - [LangChain](https://composio.dev/toolkits/tiktok/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/tiktok/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/tiktok/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/tiktok/framework/crew-ai) ## Related Toolkits - [Twitter](https://composio.dev/toolkits/twitter) - Twitter is a social media platform for sharing real-time updates, conversations, and news. Stay connected, informed, and engaged with communities worldwide. - [Instagram](https://composio.dev/toolkits/instagram) - Instagram is a social platform for sharing photos, videos, and stories with your audience. It helps brands and creators engage, grow, and analyze their online presence. - [Ayrshare](https://composio.dev/toolkits/ayrshare) - Ayrshare is a Social Media API for managing, automating, and analyzing posts across multiple platforms. It helps you streamline social media workflows and centralize analytics. - [Dotsimple](https://composio.dev/toolkits/dotsimple) - Dotsimple is a social media management platform for planning, creating, and publishing content. It helps teams boost their reach with AI-powered content generation and actionable analytics. - [Strava](https://composio.dev/toolkits/strava) - Strava is a social fitness network and app for cyclists and runners. It's perfect for tracking workouts, sharing progress, and joining active communities. - [Gmail](https://composio.dev/toolkits/gmail) - Gmail is Google's email service with powerful spam protection, search, and G Suite integration. It keeps your inbox organized and makes communication fast and reliable. - [Google Calendar](https://composio.dev/toolkits/googlecalendar) - Google Calendar is a time management service for scheduling meetings, events, and reminders. It streamlines personal and team organization with integrated notifications and sharing options. - [Google Drive](https://composio.dev/toolkits/googledrive) - Google Drive is a cloud storage platform for uploading, sharing, and collaborating on files. It's perfect for keeping your documents accessible and organized across devices. - [Outlook](https://composio.dev/toolkits/outlook) - Outlook is Microsoft's email and calendaring platform for unified communications and scheduling. It helps users stay organized with powerful email, contacts, and calendar management. - [Google Sheets](https://composio.dev/toolkits/googlesheets) - Google Sheets is a cloud-based spreadsheet tool for real-time collaboration and data analysis. It lets teams work together from anywhere, updating information instantly. - [Supabase](https://composio.dev/toolkits/supabase) - Supabase is an open-source backend platform offering scalable Postgres databases, authentication, storage, and real-time APIs. It lets developers build modern apps without managing infrastructure. - [Composio](https://composio.dev/toolkits/composio) - Composio is an integration platform that connects AI agents with hundreds of business tools. It streamlines authentication and lets you trigger actions across services—no custom code needed. - [Notion](https://composio.dev/toolkits/notion) - Notion is a collaborative workspace for notes, docs, wikis, and tasks. It streamlines team knowledge, project tracking, and workflow customization in one place. - [Slack](https://composio.dev/toolkits/slack) - Slack is a channel-based messaging platform for teams and organizations. It helps people collaborate in real time, share files, and connect all their tools in one place. - [Airtable](https://composio.dev/toolkits/airtable) - Airtable combines the flexibility of spreadsheets with the power of a database for easy project and data management. Teams use Airtable to organize, track, and collaborate with custom views and automations. - [Google Docs](https://composio.dev/toolkits/googledocs) - Google Docs is a cloud-based word processor that enables document creation and real-time collaboration. Its seamless sharing and version history make team editing and content management a breeze. - [Google Super](https://composio.dev/toolkits/googlesuper) - Google Super is an all-in-one suite combining Gmail, Drive, Calendar, Sheets, Analytics, and more. It gives you a unified platform to manage your digital life, boosting productivity and organization. - [Hubspot](https://composio.dev/toolkits/hubspot) - HubSpot is an all-in-one marketing, sales, and customer service platform. It lets teams nurture leads, automate outreach, and track every customer interaction in one place. - [Codeinterpreter](https://composio.dev/toolkits/codeinterpreter) - Codeinterpreter is a Python-based coding environment with built-in data analysis and visualization. It lets you instantly run scripts, plot results, and prototype solutions inside supported platforms. - [Gong](https://composio.dev/toolkits/gong) - Gong is a platform for video meetings, call recording, and team collaboration. It helps teams capture conversations, analyze calls, and turn insights into action. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Tiktok MCP? With a standalone Tiktok MCP server, the agents and LLMs can only access a fixed set of Tiktok tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Tiktok 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 Tiktok tools. ### Can I manage the permissions and scopes for Tiktok while using Tool Router? Yes, absolutely. You can configure which Tiktok 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 Tiktok data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)