How to integrate Missive MCP with LangChain

This guide walks you through connecting Missive to LangChain using the Composio tool router. By the end, you'll have a working Missive agent that can list all team members for marketing, create a draft email for client follow-up, send a chat message in project conversation through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Missive account through Composio's Missive MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Missive

Api Key

Missive is a collaborative email and chat app for teams to manage conversations and tasks together. It helps streamline team inboxes, shared labels, and internal discussion in one place.

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Introduction

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

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

Also integrate Missive 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 Missive project to Composio
Create a Tool Router MCP session for Missive
Initialize an MCP client and retrieve Missive tools
Build a LangChain agent that can interact with Missive
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 Missive MCP server, and what's possible with it?

The Missive MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Missive account. It provides structured and secure access to your team's shared inboxes and chat threads, so your agent can perform actions like drafting emails, sending messages, generating reports, and managing team communication on your behalf.

Automated message drafting and scheduling: Let your agent create and save email, SMS, WhatsApp, or live chat drafts for later editing or scheduled sending.
Instant message sending in conversations: Have your agent send new messages directly to any Missive conversation, keeping your team in the loop in real time.
Team and user management: Effortlessly list all teams and their members, or pull a full directory of users in your Missive organization for easy coordination and task assignment.
Analytics report generation: Direct your agent to create detailed analytics reports across time ranges and filters, helping your team track productivity and engagement.
Webhook automation setup: Enable your agent to create or delete webhook subscriptions, so you can automate notifications and integrations with other tools as needed.

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 Missive 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 Missive 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: ['missive']
    }
);

const url = session.mcp.url;

What's happening:

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

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "missive-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 Missive MCP server via HTTP
The client is configured with a name and the URL from our Tool Router session
getTools() retrieves all available Missive 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 Missive 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 Missive 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: ['missive']
        }
    );

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

Create Analytics Report

Tool to create an analytics report.

Create Missive Contacts

Tool to create one or more contacts in a Missive contact book.

Create Draft

Tool to create a new draft in Missive.

Create Missive Post

Tool to create a post in a Missive conversation.

Create Canned Response

Tool to create one or more canned responses (templates) in Missive.

Create Shared Label

Tool to create one or more shared labels at the organization level.

Create Missive Task

Tool to create a task in Missive.

Create Team

Tool to create a new team in an organization.

Create Webhook

Tool to create a webhook subscription.

Delete Draft

Tool to delete a draft from a conversation by draft ID.

Delete Post

Tool to delete a post from a conversation by post ID.

Delete Saved Responses

Tool to delete one or more saved responses by ID.

Delete Webhook

Tool to delete a webhook subscription by webhook ID.

Get Analytics Report

Tool to fetch a completed analytics report using its ID.

Get Missive Contact

Tool to fetch a specific contact using the contact ID.

Get Missive Conversation

Tool to fetch full conversation metadata (assignees/users/labels/team/org) for a specific conversation ID.

List Conversation Messages

Tool to list messages belonging to a Missive conversation (newest first).

Get Missive Message

Tool to fetch full message details including headers, HTML body, and attachments.

Get Missive Response

Tool to fetch a specific saved response using the response ID.

Get Missive Task

Tool to get a single task by ID with full details including assignees, team, and conversation info.

List Missive Contact Books

Tool to list contact books the authenticated user has access to.

List Missive Contact Groups

Tool to list contact groups or organizations linked to a contact book.

List Missive Contacts

Tool to list contacts from a contact book.

List Conversation Comments

Tool to list comments in a Missive conversation ordered from newest to oldest.

List Conversation Drafts

Tool to list draft messages in a Missive conversation (newest first).

List Conversation Posts

Tool to list posts in a Missive conversation ordered by newest first.

List Missive Conversations

Tool to list conversations visible to the authenticated user ordered by newest activity first.

List Messages by Message-ID

Tool to fetch messages matching an email Message-ID header.

List Missive Organizations

Tool to list organizations the authenticated user is part of.

List Missive Saved Responses

Tool to list saved responses (canned responses/templates) for the authenticated user.

List Missive Shared Labels

Tool to list shared labels (organization-level labels) available to the authenticated user.

List Missive Tasks

Tool to list tasks accessible to the authenticated user.

List Missive Teams

Tool to list all teams.

List Missive Users

Tool to list all users.

Merge Missive Conversations

Tool to merge multiple conversations into one.

Update Missive Contact

Tool to update one or more contacts in Missive.

Update Saved Response

Tool to update one or more saved responses in Missive.

Update Shared Labels

Tool to update one or more shared labels in Missive.

Update Missive Task

Tool to update an existing task's attributes in Missive.

Update Missive Team

Tool to update one or more teams in Missive.

FRAMEWORKS

How to build Missive MCP Agent with another framework

OpenAI Agents SDK

Use Missive MCP with OpenAI Agents SDK

Claude Agent SDK

Use Missive MCP with Claude Agent SDK

Claude Code

Use Missive MCP with Claude Code

Claude Cowork

Use Missive MCP with Claude Cowork

Codex

Use Missive MCP with Codex

OpenClaw

Use Missive MCP with OpenClaw

Hermes

Use Missive MCP with Hermes

CLI

Use Missive MCP with CLI

Google ADK

Use Missive MCP with Google ADK

Vercel AI SDK

Use Missive MCP with Vercel AI SDK

Mastra AI

Use Missive MCP with Mastra AI

LlamaIndex

Use Missive MCP with LlamaIndex

CrewAI

Use Missive MCP with CrewAI

MORE TOOLKITS

Explore Other Toolkits

Toolkit marketplace

Gmail

Oauth2

Gmail is Google's email service with powerful spam protection, search, and G Suite integration. It keeps your inbox organized and makes communication fast and reliable.

Outlook

Oauth2S2s Oauth2

Outlook is Microsoft's email and calendaring platform for unified communications and scheduling. It helps users stay organized with powerful email, contacts, and calendar management.

Slack

Oauth2

Slack is a channel-based messaging platform for teams and organizations. It helps people collaborate in real time, share files, and connect all their tools in one place.

Gong

BasicOauth2

Gong is a platform for video meetings, call recording, and team collaboration. It helps teams capture conversations, analyze calls, and turn insights into action.

FAQ

Frequently asked questions

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

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

Start with Missive.It takes 30 seconds.

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

Start building

Customer stories

Teams ship real agents on Composio

GET STARTED FOR FREE BOOK A DEMO

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 Missive MCP with LangChain

Connect Missive without auth hassles

Introduction

Also integrate Missive with

TL;DR

What is LangChain?

What is the Missive 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 Missive 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

Gmail

Outlook

Slack

Gong

Frequently asked questions

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

Can I use Tool Router MCP with LangChain?+

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

How safe is my data with Composio Tool Router?+

Start with Missive.It takes 30 seconds.

Teams ship real agents on Composio