How to integrate Amazing Marvin MCP with LangChain

This guide walks you through connecting Amazing Marvin to LangChain using the Composio tool router. By the end, you'll have a working Amazing Marvin agent that can create your tasks, complete tasks, manage projects, set reminders, and track your time through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Amazing Marvin account through Composio's Amazing Marvin MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Amazing Marvin is a personal productivity app for tasks, projects, habits, planning, time tracking, and rewards. It helps you build a flexible workflow that matches how you actually work.

10 Tools

Introduction

This guide walks you through connecting Amazing Marvin to LangChain using the Composio tool router. By the end, you'll have a working Amazing Marvin agent that can create your tasks, complete tasks, manage projects, set reminders, and track your time through natural language commands.

This guide will help you understand how to give your LangChain agent real control over a Amazing Marvin account through Composio's Amazing Marvin MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Amazing Marvin with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Connect your Amazing Marvin project to Composio
  • Create a Tool Router MCP session for Amazing Marvin
  • Initialize an MCP client and retrieve Amazing Marvin tools
  • Build a LangChain agent that can interact with Amazing Marvin
  • Set up an interactive chat interface for testing

What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.

Key features include:

  • Agent Framework: Build agents that can use tools and make decisions
  • MCP Integration: Connect to external services through Model Context Protocol adapters
  • Memory Management: Maintain conversation history across interactions
  • Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

What is the Amazing Marvin MCP server, and what's possible with it?

The Amazing Marvin MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Amazing Marvin account. It provides structured and secure access to your tasks, projects, planning items, reminders, labels, and time tracking, so your agent can create and complete tasks, organize projects, manage reminders, review plans, and track time on your behalf.

  • Task and project management: Have your agent create tasks and projects with schedules, priorities, estimates, notes, labels, and project organization, or mark finished tasks complete.
  • Planning and workload review: Let the agent list open items, check what is scheduled for a specific date, or review work due by a chosen date.
  • Reminder management: Direct your agent to review scheduled reminders, set mobile push reminders, replace existing reminders, or delete reminders you no longer need.
  • Time tracking control: Instruct your agent to check which task is currently being tracked, start tracking time for a task, or stop the active timer.
  • Category and label organization: Have your agent list your available categories or labels, then use them to organize new tasks and projects.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step10 STEPS
1

Prerequisites

Before starting this tutorial, make sure you have:
  • Python 3.10 or higher installed on your system
  • A Composio account with an API key
  • An OpenAI API key
  • Basic familiarity with Python and async programming
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard 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.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.
3

Install dependencies

npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters dotenv

Install the required packages for LangChain with MCP support.

What's happening:

  • @composio/langchain provides Composio integration for LangChain
  • @langchain/mcp-adapters enables MCP client connections
  • @langchain/core is the core agent framework
  • dotenv/config loads environment variables
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your requests to Composio's API
  • COMPOSIO_USER_ID identifies the user for session management
  • OPENAI_API_KEY enables access to OpenAI's language models
5

Import dependencies

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

dotenv.config();
What's happening:
  • We're importing LangChain's MCP adapter and Composio SDK
  • The dotenv/config import loads environment variables from your .env file
  • This setup prepares the foundation for connecting LangChain with Amazing Marvin functionality through MCP
6

Initialize Composio client

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });
What's happening:
  • We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
  • Creating a Composio instance that will manage our connection to Amazing Marvin tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding
7

Create a Tool Router session

const session = await composio.create(
    userId as string,
    {
        toolkits: ['amazing_marvin']
    }
);

const url = session.mcp.url;
What's happening:
  • We're creating a Tool Router session that gives your agent access to Amazing Marvin tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned session.mcp.url is the MCP server URL that your agent will use
  • This approach allows the agent to dynamically load and use Amazing Marvin tools as needed
8

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "amazing_marvin-agent": {
        transport: "http",
        url: url,
        headers: {
            "x-api-key": process.env.COMPOSIO_API_KEY
        }
    }
});

const tools = await client.getTools();

const agent = createAgent({ model: "gpt-5", tools });
What's happening:
  • We're creating a MultiServerMCPClient that connects to our Amazing Marvin MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • getTools() retrieves all available Amazing Marvin tools that the agent can use
  • We're creating a LangChain agent using the GPT-5 model
9

Set up interactive chat interface

let conversationHistory: any[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log("Ask any Amazing Marvin related question or task to the agent.\n");

const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: '
});

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;
    }

    conversationHistory.push({ role: "user", content: trimmedInput });
    console.log("\nAgent is thinking...\n");

    const response = await agent.invoke({ messages: conversationHistory });
    conversationHistory = response.messages;

    const finalResponse = response.messages[response.messages.length - 1]?.content;
    console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\n👋 Session ended.');
        process.exit(0);
    });
What's happening:
  • We initialize an empty conversationHistory list to maintain context across interactions
  • A readline interface is used to continuously accept user input from the command line
  • When a user types a message, it's added to the conversation history and sent to the agent
  • The agent processes the request using the invoke() method with the full conversation history
  • Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully
10

Run the application

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});
What's happening:
  • We call the main() function to start the application

Complete Code

Here's the complete code to get you started with Amazing Marvin and LangChain:

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";  
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });

    const session = await composio.create(
        userId as string,
        {
            toolkits: ['amazing_marvin']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "amazing_marvin-agent": {
            transport: "http",
            url: url,
            headers: {
                "x-api-key": process.env.COMPOSIO_API_KEY
            }
        }
    });
    
    const tools = await client.getTools();
  
    const agent = createAgent({ model: "gpt-5", tools });
    
    let conversationHistory: any[] = [];
    
    console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
    console.log("Ask any Amazing Marvin related question or task to the agent.\n");
    
    const rl = readline.createInterface({
        input: process.stdin,
        output: process.stdout,
        prompt: 'You: '
    });

    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;
        }
        
        conversationHistory.push({ role: "user", content: trimmedInput });
        console.log("\nAgent is thinking...\n");
        
        const response = await agent.invoke({ messages: conversationHistory });
        conversationHistory = response.messages;
        
        const finalResponse = response.messages[response.messages.length - 1]?.content;
        console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\nSession ended.');
        process.exit(0);
    });
}

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});

Conclusion

You've successfully built a LangChain agent that can interact with Amazing Marvin through Composio's Tool Router.

Key features of this implementation:

  • Dynamic tool loading through Composio's Tool Router
  • Conversation history maintenance for context-aware responses
  • Async Python provides clean, efficient execution of agent workflows
You can extend this further by adding error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.
TOOLS

Supported Tools

Every Amazing Marvin action and event your agent gets out of the box.

Complete Task

Mark one task complete using Amazing Marvin's experimental completion endpoint.

Create Project

Create a project with optional hierarchy, planning, priority, estimate, labels, and notes.

Create Task

Create a task with optional scheduling, organization, estimate, and note fields; title autocompletion is enabled by default.

Delete Reminders

Permanently delete only the specified Amazing Marvin reminders by exact ID.

Get Current Time Tracking

Return the task currently being time-tracked, or tracked=false when no timer is active.

List Categories or Labels

List categories or labels so their IDs can be used when creating and organizing Amazing Marvin tasks and projects.

List Planning Items

List open child items, items scheduled for a date, or items due by a date; choose one view per call.

List Reminders

List all currently scheduled Amazing Marvin reminders.

Set Reminders

Create or replace one or more mobile push reminders using caller-supplied reminder IDs.

Set Time Tracking

Start or stop time tracking for one task.

FRAMEWORKS

How to build Amazing Marvin MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Amazing Marvin MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Amazing Marvin MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Amazing Marvin MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Amazing Marvin MCP with Claude Cowork

Codex logo

Codex

Use Amazing Marvin MCP with Codex

OpenClaw logo

OpenClaw

Use Amazing Marvin MCP with OpenClaw

Hermes logo

Hermes

Use Amazing Marvin MCP with Hermes

CLI logo

CLI

Use Amazing Marvin MCP with CLI

Google ADK logo

Google ADK

Use Amazing Marvin MCP with Google ADK

Vercel AI SDK logo

Vercel AI SDK

Use Amazing Marvin MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Amazing Marvin MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Amazing Marvin MCP with LlamaIndex

CrewAI logo

CrewAI

Use Amazing Marvin MCP with CrewAI

FAQ

Frequently asked questions

With a standalone Amazing Marvin MCP server, the agents and LLMs can only access a fixed set of Amazing Marvin tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Amazing Marvin and many other apps based on the task at hand, all through a single MCP endpoint.

Yes, you can. LangChain 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 Amazing Marvin tools.

Yes, absolutely. You can configure which Amazing Marvin 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.

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 Amazing Marvin data and credentials are handled as safely as possible.

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