# How to integrate Junglescout MCP with Mastra AI ```json { "title": "How to integrate Junglescout MCP with Mastra AI", "toolkit": "Junglescout", "toolkit_slug": "junglescout", "framework": "Mastra AI", "framework_slug": "mastra-ai", "url": "https://composio.dev/toolkits/junglescout/framework/mastra-ai", "markdown_url": "https://composio.dev/toolkits/junglescout/framework/mastra-ai.md", "updated_at": "2026-05-12T10:16:35.868Z" } ``` ## Introduction This guide walks you through connecting Junglescout to Mastra AI using the Composio tool router. By the end, you'll have a working Junglescout agent that can show sales estimates for your top products, get historical search volume for 'wireless earbuds', find keywords where your asin ranks high through natural language commands. This guide will help you understand how to give your Mastra AI agent real control over a Junglescout account through Composio's Junglescout MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Junglescout with - [OpenAI Agents SDK](https://composio.dev/toolkits/junglescout/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/junglescout/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/junglescout/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/junglescout/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/junglescout/framework/codex) - [OpenClaw](https://composio.dev/toolkits/junglescout/framework/openclaw) - [Hermes](https://composio.dev/toolkits/junglescout/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/junglescout/framework/cli) - [Google ADK](https://composio.dev/toolkits/junglescout/framework/google-adk) - [LangChain](https://composio.dev/toolkits/junglescout/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/junglescout/framework/ai-sdk) - [LlamaIndex](https://composio.dev/toolkits/junglescout/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/junglescout/framework/crew-ai) ## TL;DR Here's what you'll learn: - Set up your environment so Mastra, OpenAI, and Composio work together - Create a Tool Router session in Composio that exposes Junglescout tools - Connect Mastra's MCP client to the Composio generated MCP URL - Fetch Junglescout tool definitions and attach them as a toolset - Build a Mastra agent that can reason, call tools, and return structured results - Run an interactive CLI where you can chat with your Junglescout agent ## What is Mastra AI? Mastra AI is a TypeScript framework for building AI agents with tool support. It provides a clean API for creating agents that can use external services through MCP. Key features include: - MCP Client: Built-in support for Model Context Protocol servers - Toolsets: Organize tools into logical groups - Step Callbacks: Monitor and debug agent execution - OpenAI Integration: Works with OpenAI models via @ai-sdk/openai ## What is the Junglescout MCP server, and what's possible with it? The Junglescout MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Junglescout account. It provides structured and secure access to Amazon product insights, so your agent can perform actions like product research, sales estimation, keyword analysis, and competitive tracking on your behalf. - Comprehensive product database queries: Direct your agent to search Jungle Scout’s product database using specific filters, so you can quickly identify profitable Amazon products based on criteria like price, rank, sales, reviews, and more. - Historical keyword search analysis: Retrieve detailed historical search volume data for any keyword, letting your agent uncover trends and demand patterns to guide your product or marketing strategy. - ASIN-based keyword discovery: Have your agent find which keywords a set of ASINs rank for on Amazon, helping you analyze competitors or optimize your own listings. - Sales estimates and revenue projections: Effortlessly ask your agent to fetch sales estimates for specific products or niches, making inventory planning and revenue forecasting a breeze. - Share of voice and competitive analysis: Let your agent pull share of voice data for your target keywords, giving you insights into brand visibility and the competitive landscape in your market. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `JUNGLESCOUT_KEYWORD_HISTORICAL_VOLUME` | Retrieve historical search volume data for a keyword | Fetches the historical search volume data for a specified keyword over a given time period. | | `JUNGLESCOUT_QUERY_THE_PRODUCT_DATABASE` | Query the product database | Queries the Jungle Scout product database to retrieve product data based on various filters. Compatible parameters include marketplace, sort, page_size, product_tiers, seller_types, categories, exclude_top_brands, exclude_unavailable_products, min_price, max_price, min_net, max_net, min_rank, max_rank, min_sales, max_sales, min_revenue, max_revenue, min_reviews, max_reviews, min_rating, max_rating, min_weight, max_weight, min_sellers, max_sellers, min_lqs, max_lqs, min_updated_at, and max_updated_at. | | `JUNGLESCOUT_RETRIEVE_DATA_FOR_A_SPECIFIC_KEYWORD_QUERY` | Retrieve data for a specific keyword query | Returns data based on a specific keyword query, including search volume and competition. | | `JUNGLESCOUT_RETRIEVE_KEYWORD_DATA_FOR_SPECIFIED_ASINS` | Retrieve keyword data for specified asins | Returns keywords for which the queried ASIN(s) appear in Amazon search results. For a given keyword, Jungle Scout collects up to 3 pages of Amazon keyword search results. Query up to 10 ASINs at a time. Apply filters to narrow search results. | | `JUNGLESCOUT_RETRIEVE_SALES_ESTIMATES_DATA` | Retrieve sales estimates data | Fetches sales estimates data for specified parameters. | | `JUNGLESCOUT_RETRIEVE_SHARE_OF_VOICE_DATA` | Retrieve share of voice data | Fetches share of voice data for specified keywords. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Junglescout MCP server is an implementation of the Model Context Protocol that connects your AI agent to Junglescout. It provides structured and secure access so your agent can perform Junglescout 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 starting, make sure you have: - Node.js 18 or higher - A Composio account with an active API key - An OpenAI API key - Basic familiarity with TypeScript ### 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 need credits or a connected billing setup to use the models. - Store the key somewhere safe. Composio API Key - Log in to the [Composio dashboard](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs). - Go to Settings and copy your API key. - This key lets your Mastra agent talk to Composio and reach Junglescout through MCP. ### 2. Install dependencies Install the required packages. What's happening: - @composio/core is the Composio SDK for creating MCP sessions - @mastra/core provides the Agent class - @mastra/mcp is Mastra's MCP client - @ai-sdk/openai is the model wrapper for OpenAI - dotenv loads environment variables from .env ```bash npm install @composio/core @mastra/core @mastra/mcp @ai-sdk/openai dotenv ``` ### 3. Set up environment variables Create a .env file in your project root. What's happening: - COMPOSIO_API_KEY authenticates your requests to Composio - COMPOSIO_USER_ID tells Composio which user this session belongs to - OPENAI_API_KEY lets the Mastra agent call OpenAI models ```bash COMPOSIO_API_KEY=your_composio_api_key_here COMPOSIO_USER_ID=your_user_id_here OPENAI_API_KEY=your_openai_api_key_here ``` ### 4. Import libraries and validate environment What's happening: - dotenv/config auto loads your .env so process.env.* is available - openai gives you a Mastra compatible model wrapper - Agent is the Mastra agent that will call tools and produce answers - MCPClient connects Mastra to your Composio MCP server - Composio is used to create a Tool Router session ```typescript import "dotenv/config"; import { openai } from "@ai-sdk/openai"; import { Agent } from "@mastra/core/agent"; import { MCPClient } from "@mastra/mcp"; import { Composio } from "@composio/core"; import * as readline from "readline"; import type { AiMessageType } from "@mastra/core/agent"; const openaiAPIKey = process.env.OPENAI_API_KEY; const composioAPIKey = process.env.COMPOSIO_API_KEY; const composioUserID = process.env.COMPOSIO_USER_ID; if (!openaiAPIKey) 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 as string, }); ``` ### 5. Create a Tool Router session for Junglescout What's happening: - create spins up a short-lived MCP HTTP endpoint for this user - The toolkits array contains "junglescout" for Junglescout access - session.mcp.url is the MCP URL that Mastra's MCPClient will connect to ```typescript async function main() { const session = await composio.create( composioUserID as string, { toolkits: ["junglescout"], }, ); const composioMCPUrl = session.mcp.url; console.log("Junglescout MCP URL:", composioMCPUrl); ``` ### 6. Configure Mastra MCP client and fetch tools What's happening: - MCPClient takes an id for this client and a list of MCP servers - The headers property includes the x-api-key for authentication - getTools fetches the tool definitions exposed by the Junglescout toolkit ```typescript const mcpClient = new MCPClient({ id: composioUserID as string, servers: { nasdaq: { url: new URL(composioMCPUrl), requestInit: { headers: session.mcp.headers, }, }, }, timeout: 30_000, }); console.log("Fetching MCP tools from Composio..."); const composioTools = await mcpClient.getTools(); console.log("Number of tools:", Object.keys(composioTools).length); ``` ### 7. Create the Mastra agent What's happening: - Agent is the core Mastra agent - name is just an identifier for logging and debugging - instructions guide the agent to use tools instead of only answering in natural language - model uses openai("gpt-5") to configure the underlying LLM ```typescript const agent = new Agent({ name: "junglescout-mastra-agent", instructions: "You are an AI agent with Junglescout tools via Composio.", model: "openai/gpt-5", }); ``` ### 8. Set up interactive chat interface What's happening: - messages keeps the full conversation history in Mastra's expected format - agent.generate runs the agent with conversation history and Junglescout toolsets - maxSteps limits how many tool calls the agent can take in a single run - onStepFinish is a hook that prints intermediate steps for debugging ```typescript let messages: AiMessageType[] = []; console.log("Chat started! Type 'exit' or 'quit' to end.\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({ id: crypto.randomUUID(), role: "user", content: trimmedInput, }); console.log("\nAgent is thinking...\n"); try { const response = await agent.generate(messages, { toolsets: { junglescout: composioTools, }, maxSteps: 8, }); const { text } = response; if (text && text.trim().length > 0) { console.log(`Agent: ${text}\n`); messages.push({ id: crypto.randomUUID(), role: "assistant", content: text, }); } } catch (error) { console.error("\nError:", error); } rl.prompt(); }); rl.on("close", async () => { console.log("\nSession ended."); await mcpClient.disconnect(); 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 { Agent } from "@mastra/core/agent"; import { MCPClient } from "@mastra/mcp"; import { Composio } from "@composio/core"; import * as readline from "readline"; import type { AiMessageType } from "@mastra/core/agent"; const openaiAPIKey = process.env.OPENAI_API_KEY; const composioAPIKey = process.env.COMPOSIO_API_KEY; const composioUserID = process.env.COMPOSIO_USER_ID; if (!openaiAPIKey) 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 as string }); async function main() { const session = await composio.create(composioUserID as string, { toolkits: ["junglescout"], }); const composioMCPUrl = session.mcp.url; const mcpClient = new MCPClient({ id: composioUserID as string, servers: { junglescout: { url: new URL(composioMCPUrl), requestInit: { headers: session.mcp.headers, }, }, }, timeout: 30_000, }); const composioTools = await mcpClient.getTools(); const agent = new Agent({ name: "junglescout-mastra-agent", instructions: "You are an AI agent with Junglescout tools via Composio.", model: "openai/gpt-5", }); let messages: AiMessageType[] = []; const rl = readline.createInterface({ input: process.stdin, output: process.stdout, prompt: "> ", }); rl.prompt(); rl.on("line", async (input: string) => { const trimmed = input.trim(); if (["exit", "quit"].includes(trimmed.toLowerCase())) { rl.close(); return; } messages.push({ id: crypto.randomUUID(), role: "user", content: trimmed }); const { text } = await agent.generate(messages, { toolsets: { junglescout: composioTools }, maxSteps: 8, }); if (text) { console.log(`Agent: ${text}\n`); messages.push({ id: crypto.randomUUID(), role: "assistant", content: text }); } rl.prompt(); }); rl.on("close", async () => { await mcpClient.disconnect(); process.exit(0); }); } main(); ``` ## Conclusion You've built a Mastra AI agent that can interact with Junglescout through Composio's Tool Router. You can extend this further by: - Adding other toolkits like Gmail, Slack, or GitHub - Building a web-based chat interface around this agent - Using multiple MCP endpoints to enable cross-app workflows ## How to build Junglescout MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/junglescout/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/junglescout/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/junglescout/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/junglescout/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/junglescout/framework/codex) - [OpenClaw](https://composio.dev/toolkits/junglescout/framework/openclaw) - [Hermes](https://composio.dev/toolkits/junglescout/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/junglescout/framework/cli) - [Google ADK](https://composio.dev/toolkits/junglescout/framework/google-adk) - [LangChain](https://composio.dev/toolkits/junglescout/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/junglescout/framework/ai-sdk) - [LlamaIndex](https://composio.dev/toolkits/junglescout/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/junglescout/framework/crew-ai) ## Related Toolkits - [Addresszen](https://composio.dev/toolkits/addresszen) - Addresszen is a real-time address autocomplete and verification service. It helps capture accurate, deliverable addresses with instant suggestions and validation. - [Asin data api](https://composio.dev/toolkits/asin_data_api) - Asin data api gives you detailed, real-time product data from Amazon, including price, rank, and reviews. Perfect for e-commerce pros and data-driven marketers who need instant marketplace insights. - [Baselinker](https://composio.dev/toolkits/baselinker) - BaseLinker is an all-in-one e-commerce management platform connecting stores, marketplaces, carriers, and more. It streamlines order processing, inventory control, and automates your sales operations. - [Bestbuy](https://composio.dev/toolkits/bestbuy) - Best Buy is a leading retailer offering APIs for product, store, and recommendation data. Instantly access up-to-date retail insights for smarter shopping and decision-making. - [Btcpay server](https://composio.dev/toolkits/btcpay_server) - BTCPay Server is a free, open-source, self-hosted Bitcoin payment processor. It lets merchants accept Bitcoin payments directly, cutting out middlemen and boosting privacy. - [Cdr platform](https://composio.dev/toolkits/cdr_platform) - Cdr platform is an API for purchasing carbon dioxide removal services. It enables businesses to offset emissions by accessing verified carbon removal projects. - [Cloudcart](https://composio.dev/toolkits/cloudcart) - CloudCart is an e-commerce platform for building and managing online stores. It helps businesses streamline product listings, orders, and customer engagement. - [Countdown api](https://composio.dev/toolkits/countdown_api) - Countdown API gives you real-time, structured eBay product data, reviews, and seller feedback. Perfect for powering price monitoring, product research, or marketplace analytics workflows. - [Dpd2](https://composio.dev/toolkits/dpd2) - Dpd2 is a robust email management platform for handling, sorting, and automating email workflows. Streamline your communications and boost productivity with advanced sorting, labeling, and response tools. - [Finerworks](https://composio.dev/toolkits/finerworks) - FinerWorks is an online platform for fine art and photo printing services. Artists and photographers use it to order custom prints and manage print inventory efficiently. - [Fingertip](https://composio.dev/toolkits/fingertip) - Fingertip is a business management platform for selling, booking, and customer engagement—all from a single link. It helps businesses streamline operations and connect with customers across social channels. - [Fraudlabs pro](https://composio.dev/toolkits/fraudlabs_pro) - FraudLabs Pro is an online payment fraud detection service for e-commerce and merchants. It helps minimize chargebacks and revenue loss by detecting and preventing fraudulent transactions. - [Gift up](https://composio.dev/toolkits/gift_up) - Gift Up! is a digital platform for selling, managing, and redeeming gift cards online. It streamlines promotions and gift card transactions for businesses and their customers. - [Goody](https://composio.dev/toolkits/goody) - Goody is a gifting platform that lets users send gifts and physical products without handling logistics. It streamlines gifting by managing delivery, fulfillment, and recipient experience. - [Gumroad](https://composio.dev/toolkits/gumroad) - Gumroad is a platform for selling digital products, physical goods, and memberships with a simple checkout and marketing tools. It streamlines creator payouts and helps you grow your audience effortlessly. - [Instacart](https://composio.dev/toolkits/instacart) - Instacart is an online grocery delivery and pickup service platform. It lets you discover local retailers and create shoppable lists and recipes with ease. - [Ko fi](https://composio.dev/toolkits/ko_fi) - Ko-fi is a platform that lets creators receive donations, memberships, and sales from fans. It helps creators monetize their work and grow their audience with minimal friction. - [Lemon squeezy](https://composio.dev/toolkits/lemon_squeezy) - Lemon Squeezy is a payments and subscription platform built for software companies. It makes managing payments, taxes, and customer subscriptions effortless. - [Loyverse](https://composio.dev/toolkits/loyverse) - Loyverse is a point-of-sale (POS) platform for small businesses, offering tools for sales, inventory, and customer loyalty. It helps streamline retail operations and boost customer engagement. - [Memberstack](https://composio.dev/toolkits/memberstack) - Memberstack lets you add user authentication, payments, and member management to your website—no backend code required. Easily manage your site's members and subscriptions from a single platform. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Junglescout MCP? With a standalone Junglescout MCP server, the agents and LLMs can only access a fixed set of Junglescout tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Junglescout and many other apps based on the task at hand, all through a single MCP endpoint. ### Can I use Tool Router MCP with Mastra AI? Yes, you can. Mastra AI 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 Junglescout tools. ### Can I manage the permissions and scopes for Junglescout while using Tool Router? Yes, absolutely. You can configure which Junglescout 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 Junglescout data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)