# How to integrate Leadfeeder MCP with Mastra AI ```json { "title": "How to integrate Leadfeeder MCP with Mastra AI", "toolkit": "Leadfeeder", "toolkit_slug": "leadfeeder", "framework": "Mastra AI", "framework_slug": "mastra-ai", "url": "https://composio.dev/toolkits/leadfeeder/framework/mastra-ai", "markdown_url": "https://composio.dev/toolkits/leadfeeder/framework/mastra-ai.md", "updated_at": "2026-05-12T10:17:16.709Z" } ``` ## Introduction This guide walks you through connecting Leadfeeder to Mastra AI using the Composio tool router. By the end, you'll have a working Leadfeeder agent that can show companies visiting our site today, get detailed visit history for acme corp, enrich this ip address with company info through natural language commands. This guide will help you understand how to give your Mastra AI agent real control over a Leadfeeder account through Composio's Leadfeeder MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Leadfeeder with - [ChatGPT](https://composio.dev/toolkits/leadfeeder/framework/chatgpt) - [OpenAI Agents SDK](https://composio.dev/toolkits/leadfeeder/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/leadfeeder/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/leadfeeder/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/leadfeeder/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/leadfeeder/framework/codex) - [OpenClaw](https://composio.dev/toolkits/leadfeeder/framework/openclaw) - [Hermes](https://composio.dev/toolkits/leadfeeder/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/leadfeeder/framework/cli) - [Google ADK](https://composio.dev/toolkits/leadfeeder/framework/google-adk) - [LangChain](https://composio.dev/toolkits/leadfeeder/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/leadfeeder/framework/ai-sdk) - [LlamaIndex](https://composio.dev/toolkits/leadfeeder/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/leadfeeder/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 Leadfeeder tools - Connect Mastra's MCP client to the Composio generated MCP URL - Fetch Leadfeeder 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 Leadfeeder 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 Leadfeeder MCP server, and what's possible with it? The Leadfeeder MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Leadfeeder account. It provides structured and secure access to your website visitor intelligence and lead data, so your agent can identify visiting companies, retrieve lead insights, view visit histories, and analyze custom feed configurations on your behalf. - Account discovery and management: Instantly retrieve a list of all Leadfeeder accounts you have access to, so your agent always knows where to take action. - Company identification by IP: Enrich an IP address to find out which company it represents, letting your agent quickly qualify new web visitors or prospects. - Detailed visit history retrieval: Pull comprehensive visit logs for specific leads—including date ranges—so your agent can surface engagement patterns and recent activity. - Custom feed analysis: List and review all custom feed configurations associated with your accounts, empowering your agent to segment website visitors according to your sales or marketing strategies. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `LEADFEEDER_GET_ACCOUNT` | Get Account | Tool to retrieve the details of a specific account by ID. Use when you need to get information about a particular Leadfeeder account. | | `LEADFEEDER_GET_ACCOUNTS` | Get Accounts | Tool to retrieve a list of accounts the user has access to. Use when you need to discover all available Leadfeeder accounts after authentication. | | `LEADFEEDER_GET_ALL_VISITS` | Get All Visits | Tool to retrieve all visits for a specific lead. Use when you need detailed visit history for a lead, optionally filtered by date range. | | `LEADFEEDER_GET_COMPANY_INFO_BY_IP` | Get Company Info by IP | Tool to retrieve company information based on an IP address. Use when you need to enrich an IP and obtain its company profile. Returns 404 if no match is found. | | `LEADFEEDER_GET_CUSTOM_FEEDS` | Get Custom Feeds | Retrieve all custom feeds configured for a Leadfeeder account. Custom feeds are saved filter configurations that help organize and segment company visits. Returns an empty list for accounts without premium features (402), non-existent accounts (404), or accounts with no custom feeds. Use LEADFEEDER_GET_ACCOUNTS first to obtain valid account IDs. | | `LEADFEEDER_GET_TRACKING_SCRIPT` | Get Tracking Script | Tool to retrieve the website tracking script for a given account. Use when you need to obtain the JavaScript tracking code to be inserted on webpages for visitor tracking. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Leadfeeder MCP server is an implementation of the Model Context Protocol that connects your AI agent to Leadfeeder. It provides structured and secure access so your agent can perform Leadfeeder 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 Leadfeeder 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 Leadfeeder What's happening: - create spins up a short-lived MCP HTTP endpoint for this user - The toolkits array contains "leadfeeder" for Leadfeeder 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: ["leadfeeder"], }, ); const composioMCPUrl = session.mcp.url; console.log("Leadfeeder 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 Leadfeeder 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: "leadfeeder-mastra-agent", instructions: "You are an AI agent with Leadfeeder 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 Leadfeeder 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: { leadfeeder: 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: ["leadfeeder"], }); const composioMCPUrl = session.mcp.url; const mcpClient = new MCPClient({ id: composioUserID as string, servers: { leadfeeder: { url: new URL(composioMCPUrl), requestInit: { headers: session.mcp.headers, }, }, }, timeout: 30_000, }); const composioTools = await mcpClient.getTools(); const agent = new Agent({ name: "leadfeeder-mastra-agent", instructions: "You are an AI agent with Leadfeeder 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: { leadfeeder: 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 Leadfeeder 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 Leadfeeder MCP Agent with another framework - [ChatGPT](https://composio.dev/toolkits/leadfeeder/framework/chatgpt) - [OpenAI Agents SDK](https://composio.dev/toolkits/leadfeeder/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/leadfeeder/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/leadfeeder/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/leadfeeder/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/leadfeeder/framework/codex) - [OpenClaw](https://composio.dev/toolkits/leadfeeder/framework/openclaw) - [Hermes](https://composio.dev/toolkits/leadfeeder/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/leadfeeder/framework/cli) - [Google ADK](https://composio.dev/toolkits/leadfeeder/framework/google-adk) - [LangChain](https://composio.dev/toolkits/leadfeeder/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/leadfeeder/framework/ai-sdk) - [LlamaIndex](https://composio.dev/toolkits/leadfeeder/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/leadfeeder/framework/crew-ai) ## Related Toolkits - [Aeroleads](https://composio.dev/toolkits/aeroleads) - Aeroleads is a B2B lead generation platform for finding business emails and phone numbers. Grow your sales pipeline faster with powerful prospecting tools. - [Autobound](https://composio.dev/toolkits/autobound) - Autobound is an AI-powered sales engagement platform that crafts hyper-personalized outreach and insights. It helps sales teams boost response rates and close more deals through tailored content and recommendations. - [Better proposals](https://composio.dev/toolkits/better_proposals) - Better Proposals is a web-based tool for crafting and sending professional proposals. It helps teams impress clients and close deals faster with slick, easy-to-use templates. - [Bidsketch](https://composio.dev/toolkits/bidsketch) - Bidsketch is a proposal software that helps businesses create professional proposals quickly and efficiently. It streamlines the proposal process, saving time while boosting client win rates. - [Bolna](https://composio.dev/toolkits/bolna) - Bolna is an AI platform for building conversational voice agents. It helps businesses automate support and streamline interactions through natural, voice-powered conversations. - [Botsonic](https://composio.dev/toolkits/botsonic) - Botsonic is a no-code AI chatbot builder for easily creating and deploying chatbots to your website. It empowers businesses to offer conversational experiences without writing code. - [Botstar](https://composio.dev/toolkits/botstar) - BotStar is a comprehensive chatbot platform for designing, developing, and training chatbots visually on Messenger and websites. It helps businesses automate conversations and customer interactions without coding. - [Callerapi](https://composio.dev/toolkits/callerapi) - CallerAPI is a white-label caller identification platform for branded caller ID and fraud prevention. It helps businesses boost customer trust while stopping spam, fraud, and robocalls. - [Callingly](https://composio.dev/toolkits/callingly) - Callingly is a lead response management platform that automates immediate call and text follow-ups with new leads. It helps sales teams boost response speed and close more deals by connecting seamlessly with CRMs and lead sources. - [Callpage](https://composio.dev/toolkits/callpage) - Callpage is a lead capture platform that lets businesses instantly connect with website visitors via callback. It boosts lead generation and increases your sales conversion rates. - [Clearout](https://composio.dev/toolkits/clearout) - Clearout is an AI-powered service for verifying, finding, and enriching email addresses. It boosts deliverability and helps you discover high-quality leads effortlessly. - [Clientary](https://composio.dev/toolkits/clientary) - Clientary is a platform for managing clients, invoices, projects, proposals, and more. It streamlines client work and saves you serious admin time. - [Convolo ai](https://composio.dev/toolkits/convolo_ai) - Convolo ai is an AI-powered communications platform for sales teams. It accelerates lead response and improves conversion rates by automating calls and integrating workflows. - [Delighted](https://composio.dev/toolkits/delighted) - Delighted is a customer feedback platform based on the Net Promoter System®. It helps you quickly gather, track, and act on customer sentiment. - [Docsbot ai](https://composio.dev/toolkits/docsbot_ai) - Docsbot ai is a platform that lets you build custom AI chatbots trained on your documentation. It automates customer support and content generation, saving time and improving response quality. - [Emelia](https://composio.dev/toolkits/emelia) - Emelia is an all-in-one B2B prospecting platform for cold-email, LinkedIn outreach, and prospect research. It streamlines outbound campaigns so you can find, engage, and warm up leads faster. - [Findymail](https://composio.dev/toolkits/findymail) - Findymail is a B2B data provider offering verified email and phone contacts for sales prospecting. Enhance outreach with automated exports, email verification, and CRM enrichment. - [Freshdesk](https://composio.dev/toolkits/freshdesk) - Freshdesk is customer support software with ticketing and automation tools. It helps teams streamline helpdesk operations for faster, better customer support. - [Fullenrich](https://composio.dev/toolkits/fullenrich) - FullEnrich is a B2B contact enrichment platform that aggregates emails and phone numbers from 15+ data vendors. Instantly find and verify lead contact data to boost your outreach. - [Gatherup](https://composio.dev/toolkits/gatherup) - GatherUp is a customer feedback and online review management platform. It helps businesses boost their reputation by streamlining how they collect and manage customer feedback. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Leadfeeder MCP? With a standalone Leadfeeder MCP server, the agents and LLMs can only access a fixed set of Leadfeeder tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Leadfeeder 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 Leadfeeder tools. ### Can I manage the permissions and scopes for Leadfeeder while using Tool Router? Yes, absolutely. You can configure which Leadfeeder 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 Leadfeeder data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)