How to integrate Imgix MCP with LangChain

This guide walks you through connecting Imgix to LangChain using the Composio tool router. By the end, you'll have a working Imgix agent that can auto-optimize all images in this folder, overlay company logo on product photos, extract main color palette from image through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Imgix account through Composio's Imgix MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Imgix is a real-time image processing and delivery service for developers. It helps you optimize, transform, and deliver images efficiently at any scale.

53 Tools

Introduction

This guide walks you through connecting Imgix to LangChain using the Composio tool router. By the end, you'll have a working Imgix agent that can auto-optimize all images in this folder, overlay company logo on product photos, extract main color palette from image through natural language commands.

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

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

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

The Imgix MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Imgix account. It provides structured and secure access to your image library, so your agent can perform actions like optimizing images, applying overlays, adjusting visual properties, and extracting color palettes on your behalf.

  • Real-time image optimization: Ask your agent to automatically compress, enhance, or format images for faster delivery and better quality using Imgix's auto optimization tools.
  • Dynamic overlays and blending: Direct the agent to blend images, text, or solid colors over your base images—perfect for watermarks, banners, or creative composites.
  • Precision image adjustments: Have your agent modify image brightness, contrast, and border settings to meet your design and branding needs instantly.
  • Extract and analyze color palettes: Let your agent pull color palettes from any image, making it easy to generate theme colors or analyze brand consistency.
  • Fine-tune overlay positioning: Control exactly where overlays appear on your images by specifying alignment and pixel-level positioning through your agent.

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 Imgix 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 Imgix 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: ['imgix']
    }
);

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

Configure the agent with the MCP URL

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

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

IMGIX_ADD_ASSET_FROM_ORIGIN

Tool to queue a path from your origin to be added to the Asset Manager.

Imgix Auto Optimization

Apply automatic image optimizations using imgix's auto parameter.

Blend Overlay

Tool to overlay an image, text, or color onto a base image using imgix blending parameters.

Imgix Blend Align

Tool to align the overlay relative to the base image when blending.

Blend Color Over Image

Tool to blend a solid color over an image using CSS keyword or hex.

Imgix Blend X Position

Position an overlay image horizontally on a base image using imgix's blend-x parameter.

Draw Image Border

Tool to draw a border around an image.

Adjust Image Brightness

Tool to adjust image brightness.

IMGIX_CANCEL_UPLOAD_SESSION

Tool to cancel an Imgix Asset Manager upload session.

IMGIX_CH

Tool to opt in to Client Hints.

IMGIX_CLOSE_UPLOAD_SESSION

Tool to close an Imgix Asset Manager upload session after the client uploads to the presigned URL.

Adjust Image Contrast

Tool to adjust image contrast.

IMGIX_CREATE_IMGIX_SOURCE

Tool to create and deploy a new imgix Source.

IMGIX_CREATE_UPLOAD_SESSION

Tool to create an Imgix Asset Manager upload session and return a presigned URL for client-side upload.

IMGIX_CS

Tool to set or strip output color space/profile on an Imgix image.

IMGIX_DL

Download an asset from an Imgix source with optional custom filename.

Adjust Image DPI

Tool to embed DPI (dots-per-inch) metadata for print output on an Imgix-rendered image.

Set Device Pixel Ratio

Tool to set device pixel ratio for an Imgix image.

Imgix URL Expiration

Tool to append an expiration parameter to an Imgix URL so it returns 404 after a given time.

IMGIX_FIT

Tool to control how an image fits target dimensions after resizing.

IMGIX_FM

Tool to choose output file format for the rendered asset.

Force Aspect Ratio

Tool to force a target aspect ratio on an Imgix image.

IMGIX_GET_SOURCE

Tool to retrieve details for a single imgix Source by its ID.

IMGIX_GET_UPLOAD_SESSION_STATUS

Tool to retrieve the status of an Imgix Asset Manager upload session.

IMGIX_H

Tool to set output image height in pixels or as a ratio of the source height.

Adjust Image Highlights

Tool to adjust highlight tonal mapping (−100 to 0).

IMGIX_LIST_ASSETS

Tool to retrieve a paginated list of assets in an imgix Source.

IMGIX_LIST_REPORTS

Tool to retrieve a list of all available reports for your imgix account.

IMGIX_LIST_SOURCES

Tool to list all Sources for an account.

Set Watermark Base URL

Tool to set the base URL prepended to the watermark image path.

Watermark Fit Mode

Tool to set how a watermark fits its target dimensions.

Imgix Mark Height

Tool to set watermark height on an Imgix URL in pixels or as a ratio of the watermark source.

IMGIX_MARK_PAD

Tool to set pixel padding between a watermark and the image edge or between tiled watermarks.

Watermark Width

Tool to set watermark width.

IMGIX_MASK

Tool to apply a mask to an image.

IMGIX_MAX_H

Constrain the maximum height of an imgix image.

IMGIX_MAX_W

Tool to set the maximum output width on an Imgix URL.

IMGIX_PALETTE

Tool to extract a color palette from an image in CSS or JSON form.

Set CSS Palette Prefix

Tool to set class-name prefix for CSS palette output.

IMGIX_PURGE_ASSET

Tool to purge an asset from the imgix cache.

Set Output Quality

Tool to set output quality for lossy formats.

IMGIX_RECT

Tool to select a source-image rectangle region in Imgix before other resizing.

Imgix Rotate

Tool to rotate an image on Imgix.

IMGIX_ROT_TYPE

Tool to control rotation behavior when `rot` is applied.

Text Overlay

Tool to render a single-line UTF-8 text overlay on an image.

IMGIX_TXT_ALIGN

Tool to align a text overlay on an Imgix image.

Set Text Color

Tool to set text overlay color on an Imgix image.

Set Text Font

Tool to choose font family/style for overlay text.

Set Text Outline Width

Tool to set outline width around overlay text.

Text Outline Color

Apply an outline color to text overlays on Imgix images.

IMGIX_TXT_SHAD

Set text shadow strength for imgix text overlays.

IMGIX_TXT_SIZE

Tool to set text font size in pixels.

IMGIX_UPDATE_SOURCE

Tool to update an existing imgix Source.

FRAMEWORKS

How to build Imgix MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Imgix MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Imgix MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Imgix MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Imgix MCP with Claude Cowork

Codex logo

Codex

Use Imgix MCP with Codex

OpenClaw logo

OpenClaw

Use Imgix MCP with OpenClaw

Hermes logo

Hermes

Use Imgix MCP with Hermes

CLI logo

CLI

Use Imgix MCP with CLI

Google ADK logo

Google ADK

Use Imgix MCP with Google ADK

Vercel AI SDK logo

Vercel AI SDK

Use Imgix MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Imgix MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Imgix MCP with LlamaIndex

CrewAI logo

CrewAI

Use Imgix MCP with CrewAI

FAQ

Frequently asked questions

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

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

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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
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
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
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
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
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
Jerome Leclanche
Co-Founder, Ingram Technologies