How to integrate OnlySocial MCP with LangChain

This guide walks you through connecting OnlySocial to LangChain using the Composio tool router. By the end, you'll have a working OnlySocial agent that can list your social accounts, review posts, upload media, create tags, and organize your tags through natural language commands. This guide will help you understand how to give your LangChain agent real control over a OnlySocial account through Composio's OnlySocial MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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OnlySocial is a social media management platform for workspaces, accounts, media, tags, posts, and account groups. Use it to organize and manage social publishing operations from one place.

10 Tools

Introduction

This guide walks you through connecting OnlySocial to LangChain using the Composio tool router. By the end, you'll have a working OnlySocial agent that can list your social accounts, review posts, upload media, create tags, and organize your tags through natural language commands.

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

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

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

The OnlySocial MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your OnlySocial account. It provides structured and secure access to your connected social accounts, posts, media, and tags, so your agent can review accounts, inspect posts, manage media, and organize tags on your behalf.

  • Connected account visibility: Have your agent list connected social accounts and check their providers and authorization status.
  • Post review: Let the agent browse workspace posts and retrieve a specific post with its accounts, tags, and content versions.
  • Media library management: Direct your agent to browse images and videos, inspect file details and alt text, or upload new media for future posts.
  • Tag organization: Instruct your agent to list, create, rename, recolor, or delete tags used to organize your social content.

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 OnlySocial 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 OnlySocial 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: ['onlysocial']
    }
);

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

Configure the agent with the MCP URL

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

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

Create Tag

Create a named, color-coded tag in the configured OnlySocial workspace.

Delete Tag

Permanently delete one tag from the configured OnlySocial workspace.

Get Media

Get one OnlySocial media file by UUID, including its URLs, type, and alt-text metadata returned by the provider.

Get Post

Get one OnlySocial post by UUID with its accounts, tags, and content versions.

List Social Accounts

List the social accounts connected to the configured OnlySocial workspace, including provider and authorization status.

List Media

Return one page of media files from the configured OnlySocial workspace for selection when composing posts.

List Posts

Return one page of posts from the configured OnlySocial workspace.

List Tags

List all tags in the configured OnlySocial workspace for organizing or filtering posts.

Update Tag

Replace the name and color of an existing OnlySocial tag.

Upload Media

Upload an image or video file to the configured OnlySocial workspace for later use in posts.

FRAMEWORKS

How to build OnlySocial MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use OnlySocial MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use OnlySocial MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use OnlySocial MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use OnlySocial MCP with Claude Cowork

Codex logo

Codex

Use OnlySocial MCP with Codex

OpenClaw logo

OpenClaw

Use OnlySocial MCP with OpenClaw

Hermes logo

Hermes

Use OnlySocial MCP with Hermes

CLI logo

CLI

Use OnlySocial MCP with CLI

Google ADK logo

Google ADK

Use OnlySocial MCP with Google ADK

Vercel AI SDK logo

Vercel AI SDK

Use OnlySocial MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use OnlySocial MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use OnlySocial MCP with LlamaIndex

CrewAI logo

CrewAI

Use OnlySocial MCP with CrewAI

FAQ

Frequently asked questions

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

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

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