# How to integrate Alttext ai MCP with LangChain

```json
{
  "title": "How to integrate Alttext ai MCP with LangChain",
  "toolkit": "Alttext ai",
  "toolkit_slug": "alttext_ai",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/alttext_ai/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/alttext_ai/framework/langchain.md",
  "updated_at": "2026-05-12T10:00:58.832Z"
}
```

## Introduction

This guide walks you through connecting Alttext ai to LangChain using the Composio tool router. By the end, you'll have a working Alttext ai agent that can generate alt text for new uploaded image, list images missing alt descriptions, search images by keyword in alt text through natural language commands.
This guide will help you understand how to give your LangChain agent real control over a Alttext ai account through Composio's Alttext ai MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Alttext ai with

- [OpenAI Agents SDK](https://composio.dev/toolkits/alttext_ai/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/alttext_ai/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/alttext_ai/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/alttext_ai/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/alttext_ai/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/alttext_ai/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/alttext_ai/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/alttext_ai/framework/cli)
- [Google ADK](https://composio.dev/toolkits/alttext_ai/framework/google-adk)
- [Vercel AI SDK](https://composio.dev/toolkits/alttext_ai/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/alttext_ai/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/alttext_ai/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/alttext_ai/framework/crew-ai)

## TL;DR

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

The Alttext ai MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Alttext ai account. It provides structured and secure access to your image library and account, so your agent can retrieve images, generate and search alt text, update account settings, and manage your Alttext.ai workflow on your behalf.
- Automated image library browsing: Instantly fetch and paginate through your stored images, complete with their alt text and metadata, to keep track of your visual assets.
- Keyword-based image searches: Direct your agent to search your image collection and find specific images or alt text based on custom search terms or filters.
- Account monitoring and insights: Check your Alttext.ai account configuration, review current usage limits, and monitor your plan details or webhook settings—no manual dashboard visits needed.
- Account configuration management: Let your agent update your account details, such as webhook URLs or display names, to streamline your integration and notification setup.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `ALTTEXT_AI_CREATE_BULK_IMAGES` | Bulk Create Images | Tool to bulk upload and process a CSV file of image URLs for alt text generation. Use when you need to process multiple images at once (up to 100,000 URLs). Invalid rows are returned in row_errors for debugging. |
| `ALTTEXT_AI_CREATE_IMAGE` | Create Image | Tool to add an image and generate alt text. Supports both URL and base64-encoded file upload. Use when you need to generate alt text for images, with options for custom prompts, keywords, multiple languages, and ecommerce data. Rate limited to 4 calls per second. |
| `ALTTEXT_AI_DELETE_IMAGE_BY_ASSET_ID` | Delete Image by Asset ID | Tool to delete an image from your library by its asset ID. Use when you need to remove a specific image permanently from your AltText.ai account. |
| `ALTTEXT_AI_GET_ACCOUNT` | Get Account | Tool to retrieve account settings and usage information. Use when you need to check your AltText.ai account configuration and usage limits before generating alt text. |
| `ALTTEXT_AI_GET_IMAGE_BY_ASSET_ID` | Get Image by Asset ID | Tool to retrieve detailed information about a specific image using its asset ID. Use when you need to fetch alt text, metadata, or status of a previously processed image. |
| `ALTTEXT_AI_GET_IMAGES` | Get Images | Tool to retrieve a paginated list of images in your library, including their alt text and metadata. Use when you need to browse or filter images programmatically after authentication. |
| `ALTTEXT_AI_SCRAPE_PAGE` | Scrape Page for Images | Tool to scrape a web page or HTML document and queue all images for alt text generation. Images are processed asynchronously. Does not execute JavaScript. Use when you need to batch-process images from a website or HTML content. |
| `ALTTEXT_AI_SEARCH_IMAGES` | Search Images | Search for images in your AltText.ai library by keywords. Searches through your previously processed images to find matches based on URLs, alt text content, and metadata. Useful for finding specific images in large libraries. Returns paginated results with alt text and metadata. Note: This searches your own image library, not a public image database. Images must be added via the Create Image endpoint before they can be searched. |
| `ALTTEXT_AI_UPDATE_ACCOUNT` | Update Account | Tool to update account settings (e.g., webhook_url, name). Use after confirming current account details to modify settings. |
| `ALTTEXT_AI_UPDATE_IMAGE_BY_ASSET_ID` | Update Image by Asset ID | Tool to update an image with new data including asset ID, alt text, and metadata. Use when you need to modify existing image information. Note: You cannot update the URL of an existing image. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Alttext ai MCP server is an implementation of the Model Context Protocol that connects your AI agent to Alttext ai. It provides structured and secure access so your agent can perform Alttext ai operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. Prerequisites

No description provided.

### 1. Getting API Keys for OpenAI and Composio

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) 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](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Navigate to your API settings and generate a new API key.
- Store this key securely as you'll need it for authentication.

### 2. Install dependencies

No description provided.
```python
pip install composio-langchain langchain-mcp-adapters langchain python-dotenv
```

```typescript
npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters dotenv
```

### 3. Set up environment variables

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
```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
```

### 4. Import dependencies

No description provided.
```python
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()
```

```typescript
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();
```

### 5. Initialize Composio client

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 Alttext ai tools
- Validating that COMPOSIO_USER_ID is also set before proceeding
```python
async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))

    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
```

```typescript
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()
    });
```

### 6. Create a Tool Router session

What's happening:
- We're creating a Tool Router session that gives your agent access to Alttext ai 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 Alttext ai tools as needed
```python
# Create Tool Router session for Alttext ai
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['alttext_ai']
)

url = session.mcp.url
```

```typescript
const session = await composio.create(
    userId as string,
    {
        toolkits: ['alttext_ai']
    }
);

const url = session.mcp.url;
```

### 7. Configure the agent with the MCP URL

No description provided.
```python
client = MultiServerMCPClient({
    "alttext_ai-agent": {
        "transport": "streamable_http",
        "url": session.mcp.url,
        "headers": {
            "x-api-key": os.getenv("COMPOSIO_API_KEY")
        }
    }
})

tools = await client.get_tools()

agent = create_agent("gpt-5", tools)
```

```typescript
const client = new MultiServerMCPClient({
    "alttext_ai-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 });
```

### 8. Set up interactive chat interface

No description provided.
```python
conversation_history = []

print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Alttext ai related question or task to the agent.\n")

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ['exit', 'quit', 'bye']:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_history.append({"role": "user", "content": user_input})
    print("\nAgent is thinking...\n")

    response = await agent.ainvoke({"messages": conversation_history})
    conversation_history = response['messages']
    final_response = response['messages'][-1].content
    print(f"Agent: {final_response}\n")
```

```typescript
let conversationHistory: any[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log("Ask any Alttext ai 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);
    });
```

### 9. Run the application

No description provided.
```python
if __name__ == "__main__":
    asyncio.run(main())
```

```typescript
main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});
```

## Complete Code

```python
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    
    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
    
    session = composio.create(
        user_id=os.getenv("COMPOSIO_USER_ID"),
        toolkits=['alttext_ai']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "alttext_ai-agent": {
            "transport": "streamable_http",
            "url": url,
            "headers": {
                "x-api-key": os.getenv("COMPOSIO_API_KEY")
            }
        }
    })
    
    tools = await client.get_tools()
  
    agent = create_agent("gpt-5", tools)
    
    conversation_history = []
    
    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Ask any Alttext ai related question or task to the agent.\n")
    
    while True:
        user_input = input("You: ").strip()
        
        if user_input.lower() in ['exit', 'quit', 'bye']:
            print("\nGoodbye!")
            break
        
        if not user_input:
            continue
        
        conversation_history.append({"role": "user", "content": user_input})
        print("\nAgent is thinking...\n")
        
        response = await agent.ainvoke({"messages": conversation_history})
        conversation_history = response['messages']
        final_response = response['messages'][-1].content
        print(f"Agent: {final_response}\n")

if __name__ == "__main__":
    asyncio.run(main())
```

```typescript
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: ['alttext_ai']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "alttext_ai-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 Alttext ai 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 Alttext ai 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.

## How to build Alttext ai MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/alttext_ai/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/alttext_ai/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/alttext_ai/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/alttext_ai/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/alttext_ai/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/alttext_ai/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/alttext_ai/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/alttext_ai/framework/cli)
- [Google ADK](https://composio.dev/toolkits/alttext_ai/framework/google-adk)
- [Vercel AI SDK](https://composio.dev/toolkits/alttext_ai/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/alttext_ai/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/alttext_ai/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/alttext_ai/framework/crew-ai)

## Related Toolkits

- [Figma](https://composio.dev/toolkits/figma) - Figma is a collaborative interface design tool for teams and individuals. It streamlines design workflows with real-time collaboration and easy sharing.
- [Abyssale](https://composio.dev/toolkits/abyssale) - Abyssale is a creative automation platform for generating images, videos, GIFs, PDFs, and HTML5 content programmatically. It streamlines and scales visual content production for marketing, design, and operations teams.
- [Bannerbear](https://composio.dev/toolkits/bannerbear) - Bannerbear is an API-driven platform for generating images and videos automatically at scale. It helps businesses create custom graphics, social visuals, and marketing assets using powerful templates.
- [Canva](https://composio.dev/toolkits/canva) - Canva is a drag-and-drop design suite for creating professional graphics, presentations, and marketing materials. It makes it easy for anyone to design with beautiful templates and a vast library of elements.
- [Claid ai](https://composio.dev/toolkits/claid_ai) - Claid.ai delivers AI-driven image editing APIs for tasks like background removal, upscaling, and color correction. It helps automate and enhance image workflows with powerful, developer-friendly tools.
- [Cloudinary](https://composio.dev/toolkits/cloudinary) - Cloudinary is a cloud-based platform for managing, uploading, and transforming images and videos. It streamlines media workflows and delivers optimized assets globally.
- [Cults](https://composio.dev/toolkits/cults) - Cults is a digital marketplace for 3D printing models, connecting designers and makers. It lets creators share, sell, and discover a huge variety of printable designs easily.
- [DeepImage](https://composio.dev/toolkits/deepimage) - DeepImage is an AI-powered image enhancer and upscaler. Get higher-quality images with just a few clicks.
- [Dreamstudio](https://composio.dev/toolkits/dreamstudio) - DreamStudio is Stability AI’s platform for generating and editing images with AI. It lets you easily turn ideas into stunning visuals, fast.
- [Dynapictures](https://composio.dev/toolkits/dynapictures) - Dynapictures is a cloud-based platform for generating personalized images at scale. Instantly create hundreds of custom visuals using your data sources, like Google Sheets.
- [Fal.ai](https://composio.dev/toolkits/fal_ai) - Fal.ai is a generative media platform offering 600+ AI models for images, video, voice, and audio. Developers use Fal.ai for fast, scalable access to cutting-edge generative AI tools.
- [Gamma](https://composio.dev/toolkits/gamma) - Gamma is an AI-powered platform for making beautiful, interactive presentations and documents. It lets anyone create and share engaging decks with minimal effort.
- [Html to image](https://composio.dev/toolkits/html_to_image) - Html to image converts HTML and CSS into images or captures web page screenshots. Instantly generate visuals from code or web content—no manual screenshots needed.
- [Imagior](https://composio.dev/toolkits/imagior) - Imagior is an AI-powered image generation platform that lets you create and customize images using dynamic templates and APIs. Perfect for businesses and creators needing fast, scalable visuals without design hassle.
- [Imejis io](https://composio.dev/toolkits/imejis_io) - Imejis io is an API-based image generation platform with powerful customization and template support. It lets you create and modify images in seconds, no manual design work required.
- [Imgix](https://composio.dev/toolkits/imgix) - Imgix is a real-time image processing and delivery service for developers. It helps you optimize, transform, and deliver images efficiently at any scale.
- [Kraken io](https://composio.dev/toolkits/kraken_io) - Kraken.io is an image optimization and compression platform. It helps you shrink image file sizes while keeping visual quality intact.
- [Logo dev](https://composio.dev/toolkits/logo_dev) - Logo.dev is an API and database for high-resolution company logos and brand metadata. Instantly fetch official logos from any domain without scraping or manual searching.
- [Miro](https://composio.dev/toolkits/miro) - Miro is a collaborative online whiteboard platform for teams to brainstorm, design, and manage projects visually. It streamlines teamwork by enabling real-time idea sharing, diagramming, and workflow planning in a single space.
- [Mural](https://composio.dev/toolkits/mural) - Mural is a digital whiteboard platform for distributed visual collaboration. It helps teams brainstorm, map ideas, and diagram together in real time.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Alttext ai MCP?

With a standalone Alttext ai MCP server, the agents and LLMs can only access a fixed set of Alttext ai tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Alttext ai and many other apps based on the task at hand, all through a single MCP endpoint.

### Can I use Tool Router MCP with LangChain?

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 Alttext ai tools.

### Can I manage the permissions and scopes for Alttext ai while using Tool Router?

Yes, absolutely. You can configure which Alttext ai 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.

### How safe is my data with Composio Tool Router?

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 Alttext ai data and credentials are handled as safely as possible.

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)