How to integrate Nutrient Document Web Services API MCP with LangChain

This guide walks you through connecting Nutrient Document Web Services API to LangChain using the Composio tool router. By the end, you'll have a working Nutrient Document Web Services API agent that can build documents, convert web pages to pdfs, ocr scanned pdfs, stage redactions, and add watermarks through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Nutrient Document Web Services API account through Composio's Nutrient Document Web Services API MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Nutrient Document Web Services API is a cloud document processing service for converting, OCRing, redacting, signing, and analyzing files. Use it to automate complex PDF and document workflows without running document infrastructure yourself.

11 Tools

Introduction

This guide walks you through connecting Nutrient Document Web Services API to LangChain using the Composio tool router. By the end, you'll have a working Nutrient Document Web Services API agent that can build documents, convert web pages to pdfs, ocr scanned pdfs, stage redactions, and add watermarks through natural language commands.

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

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

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

The Nutrient Document Web Services API MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Nutrient Document Web Services API account. It provides structured and secure access to document processing and account usage, so your agent can create and convert documents, OCR and improve PDFs, stage redactions, add watermarks, and check costs and usage on your behalf.

  • Document creation and conversion: Have your agent build documents from remote files, HTML, and new pages, or convert Markdown and public web pages into PDFs.
  • Searchable and accessible PDFs: Let the agent apply OCR to scanned PDFs or add screen-reader tags for PDF/UA accessibility.
  • Redaction review: Direct your agent to find matching content in a remote PDF and prepare a review copy with unapplied redaction marks.
  • PDF watermarking: Instruct your agent to add positioned text or image watermarks to every page of a PDF.
  • Cost and usage checks: Have your agent estimate a document job's required credits before processing, then review subscription status, remaining credits, and Processor usage.

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 Nutrient Document Web Services API 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 Nutrient Document Web Services API 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: ['nutrient_document_web_services_api']
    }
);

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

Configure the agent with the MCP URL

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

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "nutrient_document_web_services_api-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 Nutrient Document Web Services API 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 Nutrient Document Web Services API 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 Nutrient Document Web Services API action and event your agent gets out of the box.

Analyze Build Cost

Estimate the credits and Processor features required by Build API instructions without executing the document job or consuming credits.

Build Document

Synchronously create one document from remote files, remote HTML, new pages, and composable safe actions, returning its filename, media type, and Base64 content up to 4 MB.

Convert Markdown to PDF

Convert CommonMark or GitHub-Flavored Markdown text into a PDF using optional built-in styling, custom CSS, page layout, and syntax highlighting settings.

Create PDF from Web Page

Render an HTML web page at a public URL, with optional page layout settings, into a PDF.

Get Account Information

Return the connected Nutrient account's subscription type, status, and estimated remaining credits.

Get Processor Usage

Return the connected account's Processor subscription status and credit usage counters.

Make PDF Accessible

Auto-tag a PDF at a remote URL for PDF/UA screen-reader accessibility and return the result's filename, media type, and Base64 content up to 4 MB.

OCR PDF

Apply optical character recognition to a PDF at a remote URL and return a searchable PDF's filename, media type, and Base64 content up to 4 MB.

Revoke JWT Token

Immediately revoke a bearer token created by CREATE_JWT_TOKEN using its ID.

Stage PDF Redactions

Find matching content in a remote PDF and return a review PDF's filename, media type, and Base64 content up to 4 MB with unapplied redaction marks.

Watermark PDF

Add a positioned text or image watermark to every page of a PDF at a public URL and return the copy's filename, media type, and Base64 content up to 4 MB.

FRAMEWORKS

How to build Nutrient Document Web Services API MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

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Claude Agent SDK logo

Claude Agent SDK

Use Nutrient Document Web Services API MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Nutrient Document Web Services API MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Nutrient Document Web Services API MCP with Claude Cowork

Codex logo

Codex

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OpenClaw logo

OpenClaw

Use Nutrient Document Web Services API MCP with OpenClaw

Hermes logo

Hermes

Use Nutrient Document Web Services API MCP with Hermes

CLI logo

CLI

Use Nutrient Document Web Services API MCP with CLI

Google ADK logo

Google ADK

Use Nutrient Document Web Services API MCP with Google ADK

Vercel AI SDK logo

Vercel AI SDK

Use Nutrient Document Web Services API MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Nutrient Document Web Services API MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Nutrient Document Web Services API MCP with LlamaIndex

CrewAI logo

CrewAI

Use Nutrient Document Web Services API MCP with CrewAI

FAQ

Frequently asked questions

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

Yes, absolutely. You can configure which Nutrient Document Web Services API 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 Nutrient Document Web Services API data and credentials are handled as safely as possible.

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