How to integrate ManyReach MCP with LangChain

This guide walks you through connecting ManyReach to LangChain using the Composio tool router. By the end, you'll have a working ManyReach agent that can create outreach campaigns, add your prospects, build mailing lists, review messages, and manage your tags through natural language commands. This guide will help you understand how to give your LangChain agent real control over a ManyReach account through Composio's ManyReach MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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ManyReach

Api Key

ManyReach is a cold email outreach platform for campaigns, prospects, senders, messages, and workspaces. It helps teams run targeted outbound email programs from one place.

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Introduction

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

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

Also integrate ManyReach with

OpenAI Agents SDK Claude Agent SDK Claude Code Claude Cowork Codex OpenClaw Hermes CLI Google ADK Vercel AI SDK Mastra AI LlamaIndex CrewAI

TL;DR

Here's what you'll learn:

Get and set up your OpenAI and Composio API keys
Connect your ManyReach project to Composio
Create a Tool Router MCP session for ManyReach
Initialize an MCP client and retrieve ManyReach tools
Build a LangChain agent that can interact with ManyReach
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 ManyReach MCP server, and what's possible with it?

The ManyReach MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your ManyReach account. It provides structured and secure access to your outreach campaigns, prospects, mailing lists, senders, messages, tags, and workspace details, so your agent can create campaigns, organize prospects, review outreach messages, check senders, and manage tags on your behalf.

Campaign planning and management: Have your agent create draft campaigns, find existing campaigns by status, and update their configuration.
Prospect and mailing list organization: Let the agent create, find, and update prospects, then create, rename, or reorganize mailing lists for targeted outreach.
Message and reply review: Instruct your agent to retrieve sent messages and replies using campaign, sender, address, subject, follow-up, or CRM status filters.
Sender and tag management: Direct your agent to find sender mailboxes by connection or warmup state, and create, find, or update tags for prospects, campaigns, and senders.
Account monitoring and cleanup: Have your agent check organization details, sending credits, and data token balances, or permanently remove campaigns, prospects, mailing lists, and tags you no longer need.

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:

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

Step-by-step Guide

Step by step10 STEPS

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

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.

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

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

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 ManyReach functionality through MCP

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 ManyReach tools
Validating that COMPOSIO_USER_ID is also set before proceeding

Create a Tool Router session

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

const url = session.mcp.url;

What's happening:

We're creating a Tool Router session that gives your agent access to ManyReach 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 ManyReach tools as needed

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "manyreach-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 ManyReach MCP server via HTTP
The client is configured with a name and the URL from our Tool Router session
getTools() retrieves all available ManyReach tools that the agent can use
We're creating a LangChain agent using the GPT-5 model

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 ManyReach 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

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 ManyReach 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: ['manyreach']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "manyreach-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 ManyReach 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 ManyReach 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 ManyReach action and event your agent gets out of the box.

Create Campaign

Create and save a new draft campaign's configuration.

Create Mailing List

Create a ManyReach mailing list.

Create Prospect

Create one ManyReach prospect.

Create Tag

Create a CRM, campaign, or sender tag.

Delete Outreach Resource

Permanently and irreversibly delete exactly one campaign, prospect, mailing list, or tag by ID.

Get Account Overview

Return the authenticated ManyReach organization together with its sending-credit and data-token balances.

List Campaigns

Find campaigns in the authenticated organization, optionally filtering by lifecycle status or archived state.

List Mailing Lists

Return one page of mailing lists available for organizing and importing prospects.

List Messages

Retrieve one read-only page of reply, sent, or manually sent messages with campaign, followup, sender, CRM-status, address, and subject filters.

List Prospects

Search and filter prospects by identity, CRM status, tags, campaign membership, and existing email-validation verdict.

List Senders

Find configured sender mailboxes by folder, connection status, warmup state, or search text.

List Tags

Find CRM, campaign, or sender tags and optionally include prospect counts.

Update Campaign

Update an existing draft campaign's configuration.

Update Mailing List

Rename or move an existing ManyReach mailing list.

Update Prospect

Update contact, personalization, list, CRM, or campaign-sending eligibility fields for one ManyReach prospect by ID.

Update Tag

Update an existing tag's title and description.

FRAMEWORKS

How to build ManyReach MCP Agent with another framework

OpenAI Agents SDK

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Claude Agent SDK

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Claude Code

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Claude Cowork

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Codex

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OpenClaw

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Hermes

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CLI

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Google ADK

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Vercel AI SDK

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Mastra AI

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LlamaIndex

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CrewAI

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MORE TOOLKITS

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Adtraction

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Adtraction is an affiliate marketing platform for partner programs, tracking links, transactions, commissions, statistics, and payments. It helps advertisers and publishers manage performance marketing with clear reporting and payout workflows.

Bulk Email Checker

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Bulk Email Checker is an email verification service for checking address validity, mailbox status, domains, and mail-server signals. It helps reduce bounces, spot risky emails, and keep outreach lists cleaner before you send.

Campaign cleaner

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Campaign cleaner is an email campaign optimization tool that boosts compatibility and deliverability across email clients. It helps marketers get better results by cleaning, enhancing, and ensuring high performance for every campaign.

Deadline funnel

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Deadline Funnel lets you create personalized deadlines and timers for your marketing campaigns. It helps marketers boost conversions by adding authentic urgency to offers.

FAQ

Frequently asked questions

With a standalone ManyReach MCP server, the agents and LLMs can only access a fixed set of ManyReach tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from ManyReach 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 ManyReach tools.

Yes, absolutely. You can configure which ManyReach 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 ManyReach data and credentials are handled as safely as possible.

Start with ManyReach.It takes 30 seconds.

Managed auth, hosted MCP servers, and every ManyReach tool your agent needs.Free to start.

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Customer stories

Teams ship real agents on Composio

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Karan skipped his own birthday party to fix our critical issue. It was 10pm and he diverted his Waymo to help us instead. This really sets the bar — it shows the commitment you need when users rely on your software.

Harsha Gaddipati

Co-founder, Slashy

A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

Abhi Arya

Co-founder, Opennote

We chose Composio over Pipedream because it delivered depth where it mattered — niche tools and tricky edge cases other platforms simply ignored. That gave us confidence to scale without compromising.

Nirman Dave

CEO, Zams

As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

Ryan Yu

Founder, Extra Thursday

Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

Tomisin Jenrola

Founder & CEO, SwarmZero

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

Jerome Leclanche

Co-Founder, Ingram Technologies

How to integrate ManyReach MCP with LangChain

Connect ManyReach without auth hassles

Introduction

Also integrate ManyReach with

TL;DR

What is LangChain?

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

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

What is Composio SDK?

How the Composio SDK works

Step-by-step Guide

Prerequisites

Getting API Keys for OpenAI and Composio

Install dependencies

Set up environment variables

Import dependencies

Initialize Composio client

Create a Tool Router session

Configure the agent with the MCP URL

Set up interactive chat interface

Run the application

Complete Code

Conclusion

Supported Tools

How to build ManyReach MCP Agent with another framework

OpenAI Agents SDK

Claude Agent SDK

Claude Code

Claude Cowork

Codex

OpenClaw

Hermes

CLI

Google ADK

Vercel AI SDK

Mastra AI

LlamaIndex

CrewAI

Explore Other Toolkits

Adtraction

Bulk Email Checker

Campaign cleaner

Deadline funnel

Frequently asked questions

What are the differences in Tool Router MCP and ManyReach MCP?+

Can I use Tool Router MCP with LangChain?+

Can I manage the permissions and scopes for ManyReach while using Tool Router?+

How safe is my data with Composio Tool Router?+

Start with ManyReach.It takes 30 seconds.

Teams ship real agents on Composio