How to integrate Blooio MCP with LangChain

This guide walks you through connecting Blooio to LangChain using the Composio tool router. By the end, you'll have a working Blooio agent that can review your chats, create contacts, tag contacts, manage groups, and check poll results through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Blooio account through Composio's Blooio MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

Blooio logoBlooio
Api Key

Blooio is a stable v2 API platform for messaging, chats, contacts, groups, phone numbers, and account analytics. It gives teams a clean way to build reliable communication workflows without stitching together fragile custom APIs.

26 Tools

Introduction

This guide walks you through connecting Blooio to LangChain using the Composio tool router. By the end, you'll have a working Blooio agent that can review your chats, create contacts, tag contacts, manage groups, and check poll results through natural language commands.

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

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

Also integrate Blooio with

TL;DR

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

The Blooio MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Blooio account. It provides structured and secure access to your messages, chats, contacts, groups, phone numbers, and account insights, so your agent can send messages, manage conversations, organize contacts, coordinate groups, and review account activity on your behalf.

  • Messaging and interactive polls: Have your agent send text, attachments, replies, or native iMessage polls, check delivery details, and review poll results.
  • Chat and reaction management: Let the agent find conversations, review message history, mark chats as read, and add or remove reactions from messages.
  • Contact organization: Direct your agent to create, find, update, or delete contacts, manage their tags, and check whether they can receive iMessage, SMS, or FaceTime.
  • Messaging group coordination: Instruct your agent to create, find, rename, or delete messaging groups and review their members.
  • Account and sender oversight: Have your agent review your organization, assigned devices, message usage, available sender numbers, and fleet risk summary.

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 Blooio 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 Blooio 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: ['blooio']
    }
);

const url = session.mcp.url;
What's happening:
  • We're creating a Tool Router session that gives your agent access to Blooio 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 Blooio tools as needed
8

Configure the agent with the MCP URL

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

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

Add Contact Tags

Add or reactivate one or more free-form tags on a contact.

Create Contact

Create a contact from an E.

Create Group

Create a messaging group, optionally linking an existing iMessage chat and recording its members; new contacts may be created for unknown members.

Delete Contact

Soft-delete one contact identified by E.

Delete Group

Soft-delete a group, remove its members, and exit its linked iMessage chat when one exists.

Get Account

Return the authenticated organization, assigned devices, and message usage without exposing the API-key identifier.

Get Chat

Return detailed counts, participant context, and latest-message metadata for one conversation.

Get Contact

Return one contact by E.

Get Contact Capabilities

Check whether a contact can receive iMessage, SMS, or FaceTime before choosing a communication path.

Get Group

Return one messaging group by its grp_ identifier.

Get Message

Return one message with content, reactions, delivery status, protocol, errors, and inline-reply context.

Get Poll Results

Return a poll's definition, option vote counts, and total votes.

Get Risk Summary

Return the cached fleet risk rollup.

List Chats

Search and page through conversations, ordered by recent activity or oldest activity.

List Contacts

Search and page through organization contacts by identifier or name.

List Group Members

Page through the members recorded for a messaging group.

List Groups

Search and page through messaging groups by name.

List Messages

Page through messages in one chat with direction, time-window, and ordering filters.

List Numbers

List sender phone numbers assigned to the connected API key and their availability state.

Mark Chat Read

Mark every message in a chat as read and irreversibly send an externally visible read receipt to the sender; the receipt cannot be unsent.

Remove Contact Tags

Soft-delete one or more exact tags from a contact sequentially; if a later removal fails, earlier removals remain applied.

Send Message

Irreversibly send one or multiple text, attachment, multipart, or inline-reply messages; multi-recipient sends may create or reuse an unnamed group and may incur messaging charges.

Send Poll

Irreversibly send an interactive native iMessage poll to a chat.

Set Message Reaction

Add or remove a classic tapback or emoji reaction on a specific or relative message in a chat.

Update Contact

Set or clear the display name of an existing contact.

Update Group

Rename a group and, when linked, synchronize the new name to its iMessage chat.

FAQ

Frequently asked questions

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

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

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