How to integrate Postiz MCP with LangChain

Connect LangChain to Postiz MCP. Schedule a linkedin post for next monday, get analytics for your last facebook post, and more using natural language, with authentication handled for you.

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Postiz

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Postiz is an agentic social media scheduling tool for managing and growing your online presence. It helps you schedule posts, capture leads, and build an audience—all powered by AI.

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Introduction

This guide walks you through connecting Postiz to LangChain using the Composio tool router. By the end, you'll have a working Postiz agent that can schedule a linkedin post for next monday, get analytics for your last facebook post, list all scheduled posts for this week through natural language commands.

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

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

TL;DR

Here's what you'll learn:

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

The Postiz MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Postiz account. It provides structured and secure access to your social media posts, connected channels, groups, and media, so your agent can create drafts, schedule or publish posts, review upcoming content, update post settings, and prepare media on your behalf.

Social post creation and scheduling: Have your agent create drafts, schedule posts for later, or publish content immediately across your connected social channels.
Connected channel and group discovery: Let the agent list your available social integrations and customer groups before preparing content for the right destination.
Scheduled content review: Direct your agent to list posts planned between two dates so you can check your upcoming publishing calendar.
Post settings management: Instruct your agent to update platform-specific settings for drafts and scheduled posts that have not yet been published.
Image and video preparation: Have your agent generate images or videos, check video generation progress, or upload public media for use in social posts.

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 Postiz 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 Postiz 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: ['postiz_mcp']
    }
);

const url = session.mcp.url;

What's happening:

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

Configure the agent with the MCP URL

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

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

Ask postiz

Ask agent 'postiz' a question.

Generateimagetool

Generate image to use in a post, in case the user specified a platform that requires attachment and attachment was not provided, ask if they want to generate a picture of a video.

Generatevideooptions

All the options to generate videos, some tools might require another call to generateVideoFunction

Generatevideotool

Generate video to use in a post, in case the user specified a platform that requires attachment and attachment was not provided, ask if they want to generate a picture of a video.

Grouplist

This tool lists the available groups (customers).

Integrationlist

This tool list available integrations to schedule posts to.

Integrationscheduleposttool

Use this when the user wants to create a draft, scheduled, or immediate social media post on their connected channels, based on the integrationSchema tool.

Integrationschema

Everytime we want to schedule a social media post, we need to understand the schema of the integration.

Postsettingstool

Update the provider settings of an existing post (scheduled or draft) that was NOT published yet.

Postslisttool

List the organization's posts scheduled to be published between two dates (the same data as the "List Posts" API endpoint).

Triggertool

Use this to call a provider helper function (a methodName from the integrationSchema callable tools) that fetches provider-specific data needed for settings, like ids or search results.

Uploadfromurltool

Upload a remote image or video into the media library from a public URL.

Videofunctiontool

Sometimes when we want to generate videos we might need to get some additional information like voice_id, etc

Videostatustool

Check the status of a video generation started with 'generateVideoTool', using the jobId it returned.

FRAMEWORKS

How to build Postiz MCP Agent with another framework

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Airtable

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FAQ

Frequently asked questions

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

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

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How to integrate Postiz MCP with LangChain

Connect Postiz without auth hassles

Introduction

Also integrate Postiz with

TL;DR

What is LangChain?

What is the Postiz 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 Postiz MCP Agent with another framework

Claude Code

Cursor

ChatGPT

Claude Cowork

Antigravity

OpenAI Agents SDK

Claude Agent SDK

Codex

Grok Build

VS Code

OpenCode

OpenClaw

Hermes

Atomic Agent

Google ADK

Vercel AI SDK

Mastra AI

LlamaIndex

CrewAI

Pydantic AI

AutoGen

Explore Other Toolkits

Google Sheets

Notion

Airtable

Asana

Frequently asked questions

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

Can I use Tool Router MCP with LangChain?+

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

How safe is my data with Composio Tool Router?+

Start with Postiz.It takes 30 seconds.