# How to integrate Giphy MCP with Vercel AI SDK v6 ```json { "title": "How to integrate Giphy MCP with Vercel AI SDK v6", "toolkit": "Giphy", "toolkit_slug": "giphy", "framework": "Vercel AI SDK", "framework_slug": "ai-sdk", "url": "https://composio.dev/toolkits/giphy/framework/ai-sdk", "markdown_url": "https://composio.dev/toolkits/giphy/framework/ai-sdk.md", "updated_at": "2026-05-12T10:12:59.307Z" } ``` ## Introduction This guide walks you through connecting Giphy to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Giphy agent that can find trending cat gifs for today, get sticker variations for smile emoji, list gifs in the 'reactions' category through natural language commands. This guide will help you understand how to give your Vercel AI SDK agent real control over a Giphy account through Composio's Giphy MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Giphy with - [OpenAI Agents SDK](https://composio.dev/toolkits/giphy/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/giphy/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/giphy/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/giphy/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/giphy/framework/codex) - [OpenClaw](https://composio.dev/toolkits/giphy/framework/openclaw) - [Hermes](https://composio.dev/toolkits/giphy/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/giphy/framework/cli) - [Google ADK](https://composio.dev/toolkits/giphy/framework/google-adk) - [LangChain](https://composio.dev/toolkits/giphy/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/giphy/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/giphy/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/giphy/framework/crew-ai) ## TL;DR Here's what you'll learn: - How to set up and configure a Vercel AI SDK agent with Giphy integration - Using Composio's Tool Router to dynamically load and access Giphy 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 Giphy MCP server, and what's possible with it? The Giphy MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Giphy account. It provides structured and secure access to the world’s largest GIF and sticker library, so your agent can search for GIFs, fetch trending categories, retrieve GIF metadata, and even track analytics on user interactions automatically. - GIF and sticker search and retrieval: Instantly have your agent fetch GIFs and stickers by ID, category, or emoji for any topic or mood you need. - Browse trending categories and curated content: Let your agent pull the latest GIF categories and browse curated collections to suggest the perfect GIF for any occasion. - Access detailed GIF and sticker metadata: Retrieve comprehensive information about specific GIFs, stickers, or even groups of items by their unique IDs. - Emoji and sticker variation discovery: Explore emoji GIFs and their creative variations, making it easy to add fun reactions or flair to your app or chat. - User interaction analytics logging: Track and register when users view, click, or share GIFs, enabling smarter personalization and reporting within your workflows. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `GIPHY_ACTION_REGISTER` | Giphy Analytics Register | Tool to register user interactions (view, click, send) with a GIF for analytics. Use when you have the analytics payload, timestamp, and user ID to record the event. | | `GIPHY_CATEGORIES` | GIPHY Categories | Tool to fetch a list of GIF categories on GIPHY. Use when you need to browse available categories before selecting one. | | `GIPHY_CATEGORY_BY_ID` | GIPHY: Get Category by ID | Tool to fetch metadata for a GIF category by its unique ID. Use when you need details for a specific category identifier. | | `GIPHY_CATEGORY_GIFS` | GIPHY: Category GIFs | Tool to fetch GIFs associated with a specific GIF category. Use after retrieving category_id from the categories endpoint to get curated GIFs. | | `GIPHY_EMOJI` | GIPHY Emoji | Tool to fetch GIPHY emoji GIF objects. Use when you need a paginated list of GIPHY emojis. | | `GIPHY_EMOJI_VARIATIONS` | Emoji Variations | Tool to fetch variations for a specific emoji. Use when you have an emoji's GIF ID and want its variations. | | `GIPHY_GET_CONTENT_BY_ID` | Get Content by ID | Tool to fetch content metadata by its unique ID. Generalizes the Get GIF by ID endpoint for all content types (GIFs, Stickers, and Clips). | | `GIPHY_GET_CONTENT_BY_IDS` | Get Content by IDs | Tool to fetch metadata for multiple pieces of content (GIFs, Stickers, or Clips) by their IDs. Use when you need information on up to 100 known content IDs across any GIPHY content type. | | `GIPHY_GET_RANDOM_ID` | Giphy Get Random ID | Tool to generate a unique random ID from Giphy. Use when you need to create a unique identifier for a new user that can be used with other Giphy endpoints to personalize API responses. | | `GIPHY_RANDOM_GIF` | Giphy Random GIF | Tool to fetch a random GIF from Giphy. Use when you need a single random GIF, optionally filtered by tag or rating. Example: 'Get a random cat GIF rated G.' | | `GIPHY_RANDOM_STICKER` | Giphy Random Sticker | Tool to fetch a single random sticker. Use when you need a random sticker, optionally filtered by tag or rating. | | `GIPHY_SEARCH_CHANNELS` | GIPHY: Search Channels | Tool to search for GIPHY channels by query term. Use when you need to find channels matching a specific topic or keyword. | | `GIPHY_SEARCH_GIFS` | GIPHY: Search GIFs | Tool to search GIPHY's GIF library. Use when you need to find GIFs by keyword or phrase. | | `GIPHY_SEARCH_STICKERS` | GIPHY: Search Stickers | Tool to search GIPHY's sticker library. Use when you need to find stickers by keyword or phrase. | | `GIPHY_TAG_RANDOM` | GIPHY: Random Tag | Tool to fetch a single random tag from Giphy. Use when you need a random search term tag, optionally filtered by a query term. | | `GIPHY_TAG_RELATED` | Get Related Tags | Tool to fetch tags related to a specified tag. Use when you want to find semantically related tags for improved search suggestion. | | `GIPHY_TAG_SEARCH` | GIPHY: Tag Search | Tool to search GIPHY's tag library for autocomplete suggestions. Use when you need to generate tag suggestions for a user query. | | `GIPHY_TAG_TRENDING` | GIPHY Trending Tags | Tool to fetch the most popular search terms (tags) on GIPHY. Use when you need trending tags for content discovery. | | `GIPHY_TRANSLATE_GIF` | GIPHY Translate GIF | Tool to translate a term or phrase into a single GIF using GIPHY's special algorithm. Use when you need to convert words into the perfect GIF representation. | | `GIPHY_TRANSLATE_STICKER` | GIPHY Translate Sticker | Tool to translate a term or phrase into a single sticker using GIPHY’s translation algorithm. Use after confirming the exact phrase to visualize as a sticker. | | `GIPHY_TRENDING_GIFS` | GIPHY Trending GIFs | Tool to fetch trending GIFs from GIPHY. Use when you need the most relevant and engaging GIFs currently trending. | | `GIPHY_TRENDING_STICKERS` | Get Trending Stickers | Tool to fetch trending stickers. Use when you need the most relevant and engaging sticker GIFs currently trending. | | `GIPHY_UPLOAD_GIF` | Giphy Upload GIF | Tool to upload a GIF or video file to GIPHY. Use when you need to create a new GIPHY entry from a local file or public URL. Requires developer API key and supports optional metadata. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Giphy MCP server is an implementation of the Model Context Protocol that connects your AI agent to Giphy. It provides structured and secure access so your agent can perform Giphy 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 Giphy 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 Giphy-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: ["giphy"], }); 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 Giphy 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 giphy, 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 Giphy 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: ["giphy"], }); 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 giphy, 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 Giphy 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 Giphy MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/giphy/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/giphy/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/giphy/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/giphy/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/giphy/framework/codex) - [OpenClaw](https://composio.dev/toolkits/giphy/framework/openclaw) - [Hermes](https://composio.dev/toolkits/giphy/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/giphy/framework/cli) - [Google ADK](https://composio.dev/toolkits/giphy/framework/google-adk) - [LangChain](https://composio.dev/toolkits/giphy/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/giphy/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/giphy/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/giphy/framework/crew-ai) ## Related Toolkits - [Youtube](https://composio.dev/toolkits/youtube) - YouTube is a leading video-sharing platform for uploading, streaming, and discovering content. It empowers creators and businesses to reach global audiences and monetize their work. - [Amara](https://composio.dev/toolkits/amara) - Amara is a collaborative platform for creating and managing subtitles and captions for videos. It helps make content accessible and multilingual for global audiences. - [Cats](https://composio.dev/toolkits/cats) - Cats is an API with a huge library of cat images, breed data, and cat facts. It makes finding adorable cat photos and trivia effortless for your apps and users. - [Chatfai](https://composio.dev/toolkits/chatfai) - Chatfai is an AI platform that lets users talk to AI versions of fictional characters from books, movies, and games. It offers an engaging, interactive experience for fans to chat, roleplay, and explore creative dialogues. - [Cincopa](https://composio.dev/toolkits/cincopa) - Cincopa is a multimedia platform for uploading, managing, and customizing videos, images, and audio. It helps you deliver engaging media experiences with robust APIs and flexible integrations. - [Dungeon fighter online](https://composio.dev/toolkits/dungeon_fighter_online) - Dungeon Fighter Online (DFO) is an arcade-style, side-scrolling action RPG packed with dynamic combat and progression. Play solo or with friends to battle monsters, complete quests, and upgrade your characters. - [Elevenlabs](https://composio.dev/toolkits/elevenlabs) - Elevenlabs is an advanced AI voice generation platform for lifelike, multilingual speech synthesis. Perfect for creating natural voices for videos, apps, and business content in seconds. - [Elevenreader](https://composio.dev/toolkits/elevenreader) - Elevenreader is an AI-powered text-to-speech service by ElevenLabs that converts written content into lifelike audio. It enables fast, natural audio generation from any text. - [Epic games](https://composio.dev/toolkits/epic_games) - Epic Games is a leading video game publisher and digital storefront, known for Fortnite and Unreal Engine. It lets gamers access, manage, and purchase games all in one place. - [Fal.ai](https://composio.dev/toolkits/fal_ai) - Fal.ai is a generative media platform offering 600+ AI models for images, video, voice, and audio. Developers use Fal.ai for fast, scalable access to cutting-edge generative AI tools. - [Headout](https://composio.dev/toolkits/headout) - Headout is a global platform for booking travel experiences, tours, and entertainment. It helps users discover and secure activities at top destinations, all in one place. - [Imagekit io](https://composio.dev/toolkits/imagekit_io) - ImageKit.io is a cloud-based media management platform for image and video delivery. Instantly optimize, transform, and deliver visuals globally via a lightning-fast CDN. - [Listennotes](https://composio.dev/toolkits/listennotes) - Listennotes is a powerful podcast search engine with a massive global database. Discover, search, and curate podcasts from around the world in seconds. - [News api](https://composio.dev/toolkits/news_api) - News api is a REST API for searching and retrieving live news articles from across the web. Instantly access headlines, coverage, and breaking stories from thousands of sources. - [RAWG Video Games Database](https://composio.dev/toolkits/rawg_video_games_database) - RAWG Video Games Database is the largest video game discovery and info service. Instantly access comprehensive details, ratings, and release dates for thousands of games. - [Seat geek](https://composio.dev/toolkits/seat_geek) - SeatGeek is a live event platform offering APIs for concerts, sports, and theater data. Instantly access events, venues, and performers info for smarter ticketing and discovery. - [Shotstack](https://composio.dev/toolkits/shotstack) - Shotstack is a cloud platform for programmatically generating videos, images, and audio. Automate creative content production at scale with flexible RESTful APIs. - [Spotify](https://composio.dev/toolkits/spotify) - Spotify is a streaming service for music and podcasts with millions of tracks from artists worldwide. Enjoy personalized playlists, recommendations, and seamless listening across all your devices. - [Ticketmaster](https://composio.dev/toolkits/ticketmaster) - Ticketmaster is a global platform for event discovery, ticket sales, and live entertainment management. Get real-time access to events and streamline ticketing for fans and organizers. - [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. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Giphy MCP? With a standalone Giphy MCP server, the agents and LLMs can only access a fixed set of Giphy tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Giphy 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 Giphy tools. ### Can I manage the permissions and scopes for Giphy while using Tool Router? Yes, absolutely. You can configure which Giphy 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 Giphy data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)