# How to integrate Moz MCP with Vercel AI SDK v6 ```json { "title": "How to integrate Moz MCP with Vercel AI SDK v6", "toolkit": "Moz", "toolkit_slug": "moz", "framework": "Vercel AI SDK", "framework_slug": "ai-sdk", "url": "https://composio.dev/toolkits/moz/framework/ai-sdk", "markdown_url": "https://composio.dev/toolkits/moz/framework/ai-sdk.md", "updated_at": "2026-05-12T10:19:33.765Z" } ``` ## Introduction This guide walks you through connecting Moz to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Moz agent that can find top keywords for competitor site, audit your website for seo issues, track daily ranking of target keyword through natural language commands. This guide will help you understand how to give your Vercel AI SDK agent real control over a Moz account through Composio's Moz MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Moz with - [OpenAI Agents SDK](https://composio.dev/toolkits/moz/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/moz/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/moz/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/moz/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/moz/framework/codex) - [OpenClaw](https://composio.dev/toolkits/moz/framework/openclaw) - [Hermes](https://composio.dev/toolkits/moz/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/moz/framework/cli) - [Google ADK](https://composio.dev/toolkits/moz/framework/google-adk) - [LangChain](https://composio.dev/toolkits/moz/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/moz/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/moz/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/moz/framework/crew-ai) ## TL;DR Here's what you'll learn: - How to set up and configure a Vercel AI SDK agent with Moz integration - Using Composio's Tool Router to dynamically load and access Moz 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 Moz MCP server, and what's possible with it? The Moz MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Moz account. It provides structured and secure access to your Moz SEO suite, so your agent can perform actions like running keyword research, auditing sites, tracking keyword rankings, and analyzing competitors on your behalf. - Keyword research and suggestions: Instantly have your agent uncover high-potential keywords, analyze search volumes, and recommend keyword opportunities for your site or content strategy. - Comprehensive site audits: Let your agent scan your website for technical SEO issues, reporting on errors, warnings, and actionable improvements to boost search visibility. - Rank tracking and performance monitoring: Ask your agent to monitor keyword rankings over time, highlight position changes, and spot opportunities or threats in your SEO landscape. - Competitor domain analysis: Empower your agent to evaluate competitor sites, compare backlink profiles, and uncover gaps or strengths for strategic planning. - Backlink and authority insights: Retrieve detailed link metrics, domain authority scores, and identify valuable backlink opportunities or potentially harmful links. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `MOZ_FETCH_METADATA_INDEX` | Fetch Metadata Index | Tool to fetch current index metadata from Moz via JSON-RPC. Returns an index ID that changes when the data in the index is updated. Use when you need to track index updates or verify the current index state. | | `MOZ_FETCH_SITE_METRICS` | Fetch Site Metrics | Tool to fetch site metrics from Moz including Domain Authority, Page Authority, Spam Score, and link counts. Use when you need SEO metrics for a domain or specific URL. Returns comprehensive link and authority data. | | `MOZ_GET_GLOBAL_TOP_ROOT_DOMAINS` | Get Global Top Root Domains | Tool to get the top 500 root domains across the entire web index sorted by Domain Authority. Returns the highest authority domains globally with Domain Authority, Spam Score, and linking domains count. Use when you need to identify the most authoritative domains on the web. | | `MOZ_GET_USAGE_DATA` | Get API Usage Data | Tool to get API usage data including the number of rows consumed. Use when you need to track API usage for a specific time range or the current billing period. | | `MOZ_GLOBAL_TOP_PAGES` | Get Global Top Pages | Tool to fetch global top pages from Moz. Use when you need a paginated list of highest authority pages. | | `MOZ_INDEX_METADATA` | Get Index Metadata | Tool to fetch link index metadata from Moz. Use when you need the current index ID (which changes when the index updates) and the dates of Spam Score model updates. Use after authenticating with Moz API. | | `MOZ_LINK_STATUS` | Check Link Status | Tool to check if source URLs link to a target URL. Use when you need to verify inbound links from multiple sources to a target. | | `MOZ_LIST_GLOBAL_TOP_DOMAINS` | Get Global Top Domains | Tool to get the top ranking domains globally based on Domain Authority. Use when you need the highest authority domains in the entire Moz index. | | `MOZ_LIST_GLOBAL_TOP_PAGES` | List Global Top Pages (JSON-RPC) | Tool to fetch global top ranking pages from Moz using JSON-RPC API. Use when you need to retrieve the highest Page Authority pages in the entire Moz index. | | `MOZ_LOOKUP_QUOTA` | Lookup Quota Information | Tool to lookup API quota information including remaining rows, quota limits, and usage across different quota types. Use when you need to check current quota status without consuming quota. | | `MOZ_POST_TOP_PAGES` | Get Top Pages | Tool to fetch the top pages on a target domain from Moz. Top pages are identified as pages with the most external links. Use when you need a list of high-authority pages on a specific domain or subdomain, sorted by Page Authority or other metrics. | | `MOZ_USAGE_DATA` | Get Usage Data | Tool to fetch API usage and quota details from Moz. Use when you need to monitor current plan, quota usage, and rate limits. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Moz MCP server is an implementation of the Model Context Protocol that connects your AI agent to Moz. It provides structured and secure access so your agent can perform Moz 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 Moz 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 Moz-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: ["moz"], }); 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 Moz 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 moz, 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 Moz 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: ["moz"], }); 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 moz, 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 Moz 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 Moz MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/moz/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/moz/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/moz/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/moz/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/moz/framework/codex) - [OpenClaw](https://composio.dev/toolkits/moz/framework/openclaw) - [Hermes](https://composio.dev/toolkits/moz/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/moz/framework/cli) - [Google ADK](https://composio.dev/toolkits/moz/framework/google-adk) - [LangChain](https://composio.dev/toolkits/moz/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/moz/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/moz/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/moz/framework/crew-ai) ## Related Toolkits - [Reddit](https://composio.dev/toolkits/reddit) - Reddit is a social news platform with thriving user-driven communities (subreddits). It's the go-to place for discussion, content sharing, and viral marketing. - [Facebook](https://composio.dev/toolkits/facebook) - Facebook is a social media and advertising platform for businesses and creators. It helps you connect, share, and manage content across your public Facebook Pages. - [Linkedin](https://composio.dev/toolkits/linkedin) - LinkedIn is a professional networking platform for connecting, sharing content, and engaging with business opportunities. It's the go-to place for building your professional brand and unlocking new career connections. - [Active campaign](https://composio.dev/toolkits/active_campaign) - ActiveCampaign is a marketing automation and CRM platform for managing email campaigns, sales pipelines, and customer segmentation. It helps businesses engage customers and drive growth through smart automation and targeted outreach. - [ActiveTrail](https://composio.dev/toolkits/active_trail) - ActiveTrail is a user-friendly email marketing and automation platform. It helps you reach subscribers and automate campaigns with ease. - [Ahrefs](https://composio.dev/toolkits/ahrefs) - Ahrefs is an SEO and marketing platform for site audits, keyword research, and competitor insights. It helps you improve search rankings and drive organic traffic. - [Amcards](https://composio.dev/toolkits/amcards) - AMCards lets you create and mail personalized greeting cards online. Build stronger customer relationships with easy, automated card campaigns. - [Beamer](https://composio.dev/toolkits/beamer) - Beamer is a news and changelog platform for in-app announcements and feature updates. It helps companies boost user engagement by sharing news where users are most active. - [Benchmark email](https://composio.dev/toolkits/benchmark_email) - Benchmark Email is a platform for creating, sending, and tracking email campaigns. It's built to help you engage audiences and analyze results—all in one place. - [Bigmailer](https://composio.dev/toolkits/bigmailer) - BigMailer is an email marketing platform for managing multiple brands with white-labeling and automation. It helps teams streamline campaigns and simplify integration with Amazon SES. - [Brandfetch](https://composio.dev/toolkits/brandfetch) - Brandfetch is an API that delivers company logos, colors, and visual branding assets. It helps marketers and developers keep brand visuals consistent everywhere. - [Brevo](https://composio.dev/toolkits/brevo) - Brevo is an all-in-one email and SMS marketing platform for transactional messaging, automation, and CRM. It helps businesses engage customers and streamline communications through powerful campaign tools. - [Campayn](https://composio.dev/toolkits/campayn) - Campayn is an email marketing platform for creating, sending, and managing campaigns. It helps businesses engage contacts and grow audiences with easy-to-use tools. - [Cardly](https://composio.dev/toolkits/cardly) - Cardly is a platform for creating and sending personalized direct mail to customers. It helps businesses break through the digital clutter by getting real engagement via physical mailboxes. - [ClickSend](https://composio.dev/toolkits/clicksend) - ClickSend is a cloud-based SMS and email marketing platform for businesses. It streamlines communication by enabling quick message delivery and contact management. - [Crustdata](https://composio.dev/toolkits/crustdata) - CrustData is an AI-powered data intelligence platform for real-time company and people data. It helps B2B sales teams, AI SDRs, and investors react to live business signals. - [Curated](https://composio.dev/toolkits/curated) - Curated is a platform for collecting, curating, and publishing newsletters. It streamlines content aggregation and distribution for creators and teams. - [Customerio](https://composio.dev/toolkits/customerio) - Customer.io is a customer engagement platform for targeted messaging across email, SMS, and push. Easily automate, segment, and track communications with your audience. - [Cutt ly](https://composio.dev/toolkits/cutt_ly) - Cutt.ly is a URL shortening service for managing and analyzing links. Streamline your workflows with quick, trackable, and branded short URLs. - [Demio](https://composio.dev/toolkits/demio) - Demio is webinar software built for marketers, offering both live and automated sessions with interactive features. It helps teams engage audiences and optimize lead generation through detailed analytics. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Moz MCP? With a standalone Moz MCP server, the agents and LLMs can only access a fixed set of Moz tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Moz 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 Moz tools. ### Can I manage the permissions and scopes for Moz while using Tool Router? Yes, absolutely. You can configure which Moz 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 Moz data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)