# How to integrate Melo MCP with Mastra AI ```json { "title": "How to integrate Melo MCP with Mastra AI", "toolkit": "Melo", "toolkit_slug": "melo", "framework": "Mastra AI", "framework_slug": "mastra-ai", "url": "https://composio.dev/toolkits/melo/framework/mastra-ai", "markdown_url": "https://composio.dev/toolkits/melo/framework/mastra-ai.md", "updated_at": "2026-05-12T10:18:36.103Z" } ``` ## Introduction This guide walks you through connecting Melo to Mastra AI using the Composio tool router. By the end, you'll have a working Melo agent that can find cities with active listings in paris region, suggest location matches for 'boulogne' input, list all saved property search queries through natural language commands. This guide will help you understand how to give your Mastra AI agent real control over a Melo account through Composio's Melo MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Melo with - [OpenAI Agents SDK](https://composio.dev/toolkits/melo/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/melo/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/melo/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/melo/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/melo/framework/codex) - [OpenClaw](https://composio.dev/toolkits/melo/framework/openclaw) - [Hermes](https://composio.dev/toolkits/melo/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/melo/framework/cli) - [Google ADK](https://composio.dev/toolkits/melo/framework/google-adk) - [LangChain](https://composio.dev/toolkits/melo/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/melo/framework/ai-sdk) - [LlamaIndex](https://composio.dev/toolkits/melo/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/melo/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 Melo tools - Connect Mastra's MCP client to the Composio generated MCP URL - Fetch Melo 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 Melo 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 Melo MCP server, and what's possible with it? The Melo MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Melo account. It provides structured and secure access to real-time, deduplicated French real estate listings and market analytics, so your agent can perform actions like searching cities, suggesting locations, retrieving saved searches, and testing webhook integrations on your behalf. - City discovery and filtering: Instantly fetch and filter lists of cities to explore specific property markets or narrow down search locations. - Location autocomplete and suggestions: Have your agent suggest matching locations for partial queries, ensuring accurate and user-friendly real estate searches. - Personalized search retrieval: Retrieve and manage your saved searches to quickly revisit or update your real estate criteria. - Webhook event simulation: Test and validate webhook integrations by simulating events, making real estate workflow automation seamless. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `MELO_GET_CITIES` | Get Cities | Tool to retrieve a list of cities with optional filters. Use when you need to fetch available cities before processing location-specific data. | | `MELO_LIST_SEARCHES` | List Searches | Retrieves all property searches saved by the authenticated user from the Melo API. Use this tool to: - View all saved property searches with their filtering criteria - Check notification settings for each search - Paginate through large lists of searches - Filter searches by title or notification status - Sort searches alphabetically by title Returns search details including location filters, budget ranges, property types, and notification configurations. The API uses Hydra collection format for pagination. | | `MELO_SIMULATE_WEBHOOK` | Simulate Webhook | Simulates sending a Melo webhook event to a specified endpoint for testing webhook integrations. This tool triggers the Melo API to send a sample webhook payload (either a property match or event notification) to your specified HTTPS endpoint. Useful for testing webhook handlers before going live. The API will send realistic property data including advert details, contact information, and geographic data to your endpoint. Use this when you need to test how your webhook endpoint handles Melo notifications. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Melo MCP server is an implementation of the Model Context Protocol that connects your AI agent to Melo. It provides structured and secure access so your agent can perform Melo 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 Melo 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 Melo What's happening: - create spins up a short-lived MCP HTTP endpoint for this user - The toolkits array contains "melo" for Melo 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: ["melo"], }, ); const composioMCPUrl = session.mcp.url; console.log("Melo 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 Melo 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: "melo-mastra-agent", instructions: "You are an AI agent with Melo 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 Melo 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: { melo: 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: ["melo"], }); const composioMCPUrl = session.mcp.url; const mcpClient = new MCPClient({ id: composioUserID as string, servers: { melo: { url: new URL(composioMCPUrl), requestInit: { headers: session.mcp.headers, }, }, }, timeout: 30_000, }); const composioTools = await mcpClient.getTools(); const agent = new Agent({ name: "melo-mastra-agent", instructions: "You are an AI agent with Melo 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: { melo: 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 Melo 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 Melo MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/melo/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/melo/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/melo/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/melo/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/melo/framework/codex) - [OpenClaw](https://composio.dev/toolkits/melo/framework/openclaw) - [Hermes](https://composio.dev/toolkits/melo/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/melo/framework/cli) - [Google ADK](https://composio.dev/toolkits/melo/framework/google-adk) - [LangChain](https://composio.dev/toolkits/melo/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/melo/framework/ai-sdk) - [LlamaIndex](https://composio.dev/toolkits/melo/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/melo/framework/crew-ai) ## Related Toolkits - [Excel](https://composio.dev/toolkits/excel) - Microsoft Excel is a robust spreadsheet application for organizing, analyzing, and visualizing data. 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Get detailed environmental insights directly from your own sensors for smarter apps and automations. - [Anonyflow](https://composio.dev/toolkits/anonyflow) - Anonyflow is a service for encryption-based data anonymization and secure data sharing. It helps organizations meet GDPR, CCPA, and HIPAA data privacy compliance requirements. - [Api ninjas](https://composio.dev/toolkits/api_ninjas) - Api ninjas offers 120+ public APIs spanning categories like weather, finance, sports, and more. Developers use it to supercharge apps with real-time data and actionable endpoints. - [Api sports](https://composio.dev/toolkits/api_sports) - Api sports is a comprehensive sports data platform covering 2,000+ competitions with live scores and 15+ years of stats. Instantly access up-to-date sports information for analysis, apps, or chatbots. - [Apify](https://composio.dev/toolkits/apify) - Apify is a cloud platform for building, deploying, and managing web scraping and automation tools called Actors. 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Instantly enrich your applications with up-to-date insights on 20M+ businesses. - [Bitquery](https://composio.dev/toolkits/bitquery) - Bitquery is a blockchain data platform offering indexed, real-time, and historical data from 40+ blockchains via GraphQL APIs. Get unified, reliable access to complex on-chain data for analytics, trading, and research. - [Brightdata](https://composio.dev/toolkits/brightdata) - Brightdata is a leading web data platform offering advanced scraping, SERP APIs, and anti-bot tools. It lets you collect public web data at scale, bypassing blocks and friction. - [Builtwith](https://composio.dev/toolkits/builtwith) - BuiltWith is a web technology profiler that uncovers the technologies powering any website. Gain actionable insights into analytics, hosting, and content management stacks for smarter research and lead generation. - [Byteforms](https://composio.dev/toolkits/byteforms) - Byteforms is an all-in-one platform for creating forms, managing submissions, and integrating data. It streamlines workflows by centralizing form data collection and automation. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Melo MCP? With a standalone Melo MCP server, the agents and LLMs can only access a fixed set of Melo tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Melo 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 Melo tools. ### Can I manage the permissions and scopes for Melo while using Tool Router? Yes, absolutely. You can configure which Melo 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 Melo data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)