How to integrate ImageRouter MCP with LangChain

This guide walks you through connecting ImageRouter to LangChain using the Composio tool router. By the end, you'll have a working ImageRouter agent that can generate images, edit your images, create videos, compare models, and check your credits through natural language commands. This guide will help you understand how to give your LangChain agent real control over a ImageRouter account through Composio's ImageRouter MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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ImageRouter is an AI media generation API for creating images, videos, and text with multiple models. It gives developers one simple route to generate assets, inspect credits, and discover available models.

8 Tools

Introduction

This guide walks you through connecting ImageRouter to LangChain using the Composio tool router. By the end, you'll have a working ImageRouter agent that can generate images, edit your images, create videos, compare models, and check your credits through natural language commands.

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

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

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

The ImageRouter MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your ImageRouter account. It provides structured and secure access to ImageRouter's generative models, model details, and account credits, so your agent can generate images, edit images, create videos, produce text, and review usage on your behalf.

  • Image generation: Have your agent turn a detailed text prompt into an image using a selected ImageRouter model.
  • Image editing: Direct your agent to transform or inpaint one or more existing images provided as web links or embedded image data.
  • Video creation: Let the agent generate videos from written prompts, with optional images supplied as visual inputs.
  • Text and multimodal responses: Instruct your agent to create text completions or responses based on plain text and structured multimodal input.
  • Model and credit checks: Have your agent discover available models, review their capabilities, supported options, and pricing, then check remaining credits and usage before starting paid work.

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 ImageRouter 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 ImageRouter 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: ['imagerouter']
    }
);

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

Configure the agent with the MCP URL

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

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

Create Chat Completion

Create a non-streaming OpenAI-compatible chat completion with a paid text model.

Create Response

Create a non-streaming OpenAI Responses API result from plain text or structured multimodal input with a selected ImageRouter text model.

Edit Image

Transform or inpaint one or more existing images supplied as URLs or data URIs.

Generate Image

Generate an image from a text prompt with a selected ImageRouter model.

Generate Video

Generate a video from text and optional URL or data-URI image inputs.

Get Credits

Inspect remaining credits, cumulative usage, deposits, and optional per-key usage before making potentially paid generation calls.

Get Model

Get current capabilities, accepted parameters, and pricing for one exact ImageRouter model ID before generation.

List Models

Discover current ImageRouter model IDs, modalities, supported parameters, and pricing before generation.

FRAMEWORKS

How to build ImageRouter MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use ImageRouter MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use ImageRouter MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use ImageRouter MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use ImageRouter MCP with Claude Cowork

Codex logo

Codex

Use ImageRouter MCP with Codex

OpenClaw logo

OpenClaw

Use ImageRouter MCP with OpenClaw

Hermes logo

Hermes

Use ImageRouter MCP with Hermes

CLI logo

CLI

Use ImageRouter MCP with CLI

Google ADK logo

Google ADK

Use ImageRouter MCP with Google ADK

Vercel AI SDK logo

Vercel AI SDK

Use ImageRouter MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use ImageRouter MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use ImageRouter MCP with LlamaIndex

CrewAI logo

CrewAI

Use ImageRouter MCP with CrewAI

FAQ

Frequently asked questions

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

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

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