# How to integrate Instagram MCP with Vercel AI SDK v6 ```json { "title": "How to integrate Instagram MCP with Vercel AI SDK v6", "toolkit": "Instagram", "toolkit_slug": "instagram", "framework": "Vercel AI SDK", "framework_slug": "ai-sdk", "url": "https://composio.dev/toolkits/instagram/framework/ai-sdk", "markdown_url": "https://composio.dev/toolkits/instagram/framework/ai-sdk.md", "updated_at": "2026-05-06T08:16:38.800Z" } ``` ## Introduction This guide walks you through connecting Instagram to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Instagram agent that can get analytics for last week's posts, list your most recent instagram photos, fetch comments on your latest post through natural language commands. This guide will help you understand how to give your Vercel AI SDK agent real control over a Instagram account through Composio's Instagram MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Instagram with - [ChatGPT](https://composio.dev/toolkits/instagram/framework/chatgpt) - [OpenAI Agents SDK](https://composio.dev/toolkits/instagram/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/instagram/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/instagram/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/instagram/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/instagram/framework/codex) - [Cursor](https://composio.dev/toolkits/instagram/framework/cursor) - [VS Code](https://composio.dev/toolkits/instagram/framework/vscode) - [OpenCode](https://composio.dev/toolkits/instagram/framework/opencode) - [OpenClaw](https://composio.dev/toolkits/instagram/framework/openclaw) - [Hermes](https://composio.dev/toolkits/instagram/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/instagram/framework/cli) - [Google ADK](https://composio.dev/toolkits/instagram/framework/google-adk) - [LangChain](https://composio.dev/toolkits/instagram/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/instagram/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/instagram/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/instagram/framework/crew-ai) ## TL;DR Here's what you'll learn: - How to set up and configure a Vercel AI SDK agent with Instagram integration - Using Composio's Tool Router to dynamically load and access Instagram 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 Instagram MCP server, and what's possible with it? The Instagram MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Instagram Business or Creator account. It provides structured and secure access to your Instagram content and analytics, so your agent can publish posts, analyze insights, fetch comments, manage conversations, and more—all on your behalf. - Automated post and carousel publishing: Let your agent draft and publish single-photo, video, or multi-image carousel posts to your feed with ease. - Real-time comments retrieval: Ask your agent to fetch and organize comments from any of your Instagram posts, making it simple to engage with your audience. - Insightful analytics and reporting: Request detailed insights on individual posts or your entire account, including impressions, reach, and engagement metrics. - Direct message conversation management: Retrieve details about your Instagram DM conversations, including participants and recent messages, to help you stay connected. - Profile and media access: Instantly fetch your profile details, statistics, and all media you've posted—photos, videos, and reels—so your agent can reference or repurpose your content. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `INSTAGRAM_CREATE_CAROUSEL_CONTAINER` | Create Carousel Container | Create a draft carousel post with multiple images/videos before publishing. | | `INSTAGRAM_CREATE_MEDIA_CONTAINER` | Create Media Container | Create a draft media container for photos/videos/reels before publishing. | | `INSTAGRAM_CREATE_POST` | Create Post | Publish a draft media container to instagram (final publishing step). | | `INSTAGRAM_GET_CONVERSATION` | Get Conversation | Get details about a specific instagram dm conversation (participants, etc). | | `INSTAGRAM_GET_POST_COMMENTS` | Get Post Comments | Get comments on an instagram post. | | `INSTAGRAM_GET_POST_INSIGHTS` | Get Post Insights | Get instagram post insights/analytics (impressions, reach, engagement, etc.). | | `INSTAGRAM_GET_POST_STATUS` | Get Post Status | Check the processing status of a draft post container. | | `INSTAGRAM_GET_USER_INFO` | Get User Info | Get instagram user info including profile details and statistics. | | `INSTAGRAM_GET_USER_INSIGHTS` | Get User Insights | Get instagram account-level insights/analytics (profile views, reach, impressions, etc.). | | `INSTAGRAM_GET_USER_MEDIA` | Get User Media | Get instagram user's media (posts, photos, videos). | | `INSTAGRAM_LIST_ALL_CONVERSATIONS` | List All Conversations | List all instagram dm conversations for the authenticated user. | | `INSTAGRAM_LIST_ALL_MESSAGES` | List All Messages | List all messages from a specific instagram dm conversation. | | `INSTAGRAM_MARK_SEEN` | Mark Seen | Mark instagram dm messages as read/seen for a specific user. | | `INSTAGRAM_REPLY_TO_COMMENT` | Reply To Comment | Reply to a comment on instagram media. | | `INSTAGRAM_SEND_IMAGE` | Send Image | Send an image via instagram dm to a specific user. | | `INSTAGRAM_SEND_TEXT_MESSAGE` | Send Text Message | Send a text message to an instagram user via dm. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Instagram MCP server is an implementation of the Model Context Protocol that connects your AI agent to Instagram. It provides structured and secure access so your agent can perform Instagram 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 Instagram 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 Instagram-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: ["instagram"], }); 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 Instagram 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 instagram, 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 Instagram 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: ["instagram"], }); 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 instagram, 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 Instagram 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 Instagram MCP Agent with another framework - [ChatGPT](https://composio.dev/toolkits/instagram/framework/chatgpt) - [OpenAI Agents SDK](https://composio.dev/toolkits/instagram/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/instagram/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/instagram/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/instagram/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/instagram/framework/codex) - [Cursor](https://composio.dev/toolkits/instagram/framework/cursor) - [VS Code](https://composio.dev/toolkits/instagram/framework/vscode) - [OpenCode](https://composio.dev/toolkits/instagram/framework/opencode) - [OpenClaw](https://composio.dev/toolkits/instagram/framework/openclaw) - [Hermes](https://composio.dev/toolkits/instagram/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/instagram/framework/cli) - [Google ADK](https://composio.dev/toolkits/instagram/framework/google-adk) - [LangChain](https://composio.dev/toolkits/instagram/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/instagram/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/instagram/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/instagram/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. - [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. - [Tiktok](https://composio.dev/toolkits/tiktok) - Tiktok is a short-form video platform for creating, sharing, and discovering viral content. It helps creators and brands reach massive audiences with creative tools and global social features. - [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 Instagram MCP? With a standalone Instagram MCP server, the agents and LLMs can only access a fixed set of Instagram tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Instagram 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 Instagram tools. ### Can I manage the permissions and scopes for Instagram while using Tool Router? Yes, absolutely. You can configure which Instagram 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 Instagram data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)