# How to integrate Ocr web service MCP with LangChain

```json
{
  "title": "How to integrate Ocr web service MCP with LangChain",
  "toolkit": "Ocr web service",
  "toolkit_slug": "ocr_web_service",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/ocr_web_service/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/ocr_web_service/framework/langchain.md",
  "updated_at": "2026-05-12T10:20:27.127Z"
}
```

## Introduction

This guide walks you through connecting Ocr web service to LangChain using the Composio tool router. By the end, you'll have a working Ocr web service agent that can extract text from uploaded invoice image, check remaining ocr pages on your account, get ocr processing logs for last week through natural language commands.
This guide will help you understand how to give your LangChain agent real control over a Ocr web service account through Composio's Ocr web service MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Ocr web service with

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

## TL;DR

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

The Ocr web service MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Ocr web service account. It provides structured and secure access to your OCR operations, allowing your agent to process images, extract text, review account usage, and monitor processing logs automatically on your behalf.
- Automated image-to-text recognition: Instantly have your agent perform OCR on uploaded images or documents and retrieve extracted text, including advanced output like word coordinates and formatted files.
- Account usage monitoring: Let your agent fetch current subscription details, check remaining page credits, and stay on top of plan expiration dates for seamless workflow continuity.
- Processing log retrieval: Ask your agent to pull detailed OCR processing logs for specific date ranges, making it easy to audit, troubleshoot, or analyze past conversions.
- Credential and connection management: Have your agent securely extract and verify connection credentials from metadata whenever needed, ensuring safe and reliable access to OCR services.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `OCR_WEB_SERVICE_GET_ACCOUNT_CREDENTIALS` | Get Account Credentials | Tool to extract OCRWebService credentials (user_name, license_code) from connection metadata. Always call this before invoking OCR_WEB_SERVICE_RECOGNIZE or OCR_WEB_SERVICE_GET_ACCOUNT_INFORMATION rather than reusing cached values, as credentials may become stale. Use OCR_WEB_SERVICE_GET_ACCOUNT_INFORMATION to verify account status and quota before submitting large jobs. |
| `OCR_WEB_SERVICE_GET_ACCOUNT_INFORMATION` | Get Account Information | Retrieve OCRWebService account information including remaining pages, subscription plan, and expiration date. Use this tool to check your account status before large OCR jobs — exhausted page quotas will cause OCR_WEB_SERVICE_RECOGNIZE to fail mid-run. Returns details about your subscription including pages remaining and plan expiration. If credentials are invalid or stale, retrieve fresh user_name and license_code via OCR_WEB_SERVICE_GET_ACCOUNT_CREDENTIALS before retrying. Requires valid OCRWebService credentials (username and license code). |
| `OCR_WEB_SERVICE_OCR_WEB_SERVICE_LOG` | OCR Web Service Log | Tool to retrieve OCR processing logs for a date range on your account. Invalid credentials or bad date ranges return empty data rather than an error, so an empty result may indicate incorrect inputs rather than no logs. |
| `OCR_WEB_SERVICE_OCR_WEB_SERVICE_RECOGNIZE` | OCRWebService Recognize | Tool to call SOAP Recognize operation. Use when performing OCR on an image to retrieve text, output document, word coordinates, and errors. Consumes page quota per call; returns HTTP 429 when limits exceeded. Check quota via OCR_WEB_SERVICE_GET_ACCOUNT_INFORMATION before large jobs; batch large PDFs in ~25–50 page chunks. |

## Supported Triggers

None listed.

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

The Ocr web service MCP server is an implementation of the Model Context Protocol that connects your AI agent to Ocr web service. It provides structured and secure access so your agent can perform Ocr web service 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 Ocr web service 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 Ocr web service 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 Ocr web service tools as needed
```python
# Create Tool Router session for Ocr web service
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['ocr_web_service']
)

url = session.mcp.url
```

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

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

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

No description provided.
```python
client = MultiServerMCPClient({
    "ocr_web_service-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({
    "ocr_web_service-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 Ocr web service 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 Ocr web service 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=['ocr_web_service']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "ocr_web_service-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 Ocr web service 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: ['ocr_web_service']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "ocr_web_service-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 Ocr web service 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 Ocr web service 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 Ocr web service MCP Agent with another framework

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

## Related Toolkits

- [Google Drive](https://composio.dev/toolkits/googledrive) - Google Drive is a cloud storage platform for uploading, sharing, and collaborating on files. It's perfect for keeping your documents accessible and organized across devices.
- [Google Docs](https://composio.dev/toolkits/googledocs) - Google Docs is a cloud-based word processor that enables document creation and real-time collaboration. Its seamless sharing and version history make team editing and content management a breeze.
- [Google Super](https://composio.dev/toolkits/googlesuper) - Google Super is an all-in-one suite combining Gmail, Drive, Calendar, Sheets, Analytics, and more. It gives you a unified platform to manage your digital life, boosting productivity and organization.
- [Affinda](https://composio.dev/toolkits/affinda) - Affinda is an AI-powered document processing platform that automates data extraction from resumes, invoices, and more. It streamlines document-heavy workflows by turning files into structured, actionable data.
- [Agility cms](https://composio.dev/toolkits/agility_cms) - Agility CMS is a headless content management system for building and managing digital experiences across platforms. It lets teams update content quickly and deliver omnichannel experiences with ease.
- [Algodocs](https://composio.dev/toolkits/algodocs) - Algodocs is an AI-powered platform that automates data extraction from business documents. It delivers fast, secure, and accurate processing without templates or manual training.
- [Api2pdf](https://composio.dev/toolkits/api2pdf) - Api2Pdf is a REST API for generating PDFs from HTML, URLs, and documents using powerful engines like wkhtmltopdf and Headless Chrome. It streamlines document conversion and automation for developers and businesses.
- [Aryn](https://composio.dev/toolkits/aryn) - Aryn is an AI-powered platform for parsing, extracting, and analyzing data from unstructured documents. Use it to automate document processing and unlock actionable insights from your files.
- [Boldsign](https://composio.dev/toolkits/boldsign) - Boldsign is a digital eSignature platform for sending, signing, and tracking documents online. Organizations use it to automate agreements and manage legally binding workflows efficiently.
- [Boloforms](https://composio.dev/toolkits/boloforms) - BoloForms is an eSignature platform built for small businesses, offering unlimited signatures, templates, and forms. It simplifies digital document signing and team collaboration at a predictable, fixed price.
- [Box](https://composio.dev/toolkits/box) - Box is a cloud content management and file sharing platform for businesses. It helps teams securely store, organize, and collaborate on files from anywhere.
- [Carbone](https://composio.dev/toolkits/carbone) - Carbone is a blazing-fast report generator that turns JSON data into PDFs, Word docs, spreadsheets, and more using flexible templates. It lets you automate document creation at scale with minimal code.
- [Castingwords](https://composio.dev/toolkits/castingwords) - CastingWords is a transcription service specializing in human-powered, accurate transcripts via a simple API. Get seamless audio-to-text conversion for interviews, meetings, podcasts, and more.
- [Cloudconvert](https://composio.dev/toolkits/cloudconvert) - CloudConvert is a powerful file conversion service supporting over 200 file formats. It streamlines converting, compressing, and managing documents, media, and more, all in one place.
- [Cloudlayer](https://composio.dev/toolkits/cloudlayer) - Cloudlayer is a document and asset generation service for creating PDFs and images via API or SDKs. It lets you automate high-quality doc creation, saving dev time and reducing manual work.
- [Cloudpress](https://composio.dev/toolkits/cloudpress) - Cloudpress is a content export tool for Google Docs and Notion. It automates publishing to your favorite Content Management Systems.
- [Contentful graphql](https://composio.dev/toolkits/contentful_graphql) - Contentful graphql is a content delivery API that lets you access Contentful data using GraphQL queries. It gives you efficient, flexible ways to fetch and manage structured content for any digital project.
- [Conversion tools](https://composio.dev/toolkits/conversion_tools) - Conversion Tools is an online service for converting documents between formats such as PDF, Word, Excel, XML, and CSV. It lets you automate complex document workflows with just a few clicks.
- [Convertapi](https://composio.dev/toolkits/convertapi) - ConvertAPI is a robust file conversion service for documents, images, and spreadsheets. It streamlines programmatic format changes and lets developers automate complex workflows with a single API.
- [Craftmypdf](https://composio.dev/toolkits/craftmypdf) - CraftMyPDF is a web-based service for designing and generating PDFs with templates and live data. It streamlines document creation by automating personalized PDFs at scale.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Ocr web service MCP?

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

### Can I manage the permissions and scopes for Ocr web service while using Tool Router?

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

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