How to integrate Encodian MCP with LangChain

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Introduction

This guide walks you through connecting Encodian to LangChain using the Composio tool router. By the end, you'll have a working Encodian agent that can resize all images in project folder, extract author and page count from pdf, add custom header to every pdf file through natural language commands.

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

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

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TL;DR

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

The Encodian MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Encodian account. It provides structured and secure access to your Encodian document automation suite, so your agent can perform actions like managing files, processing PDFs, encoding or decoding content, and automating workflow tasks on your behalf.

  • File management and property retrieval: Quickly get detailed information about files, move documents between containers, and keep your Microsoft 365 storage organized automatically.
  • Document processing and automation: Direct your agent to add headers and footers to PDFs, extract PDF metadata, or resize images for seamless document formatting and compliance tasks.
  • Base64 content conversion: Effortlessly encode text or files to Base64, or decode Base64 strings back to usable files for secure data exchange and workflow integration.
  • Archive extraction and manipulation: Unzip files and retrieve their contents, making it easy to automate bulk document handling or trigger downstream processing steps.
  • Data integrity and comparison tools: Use hashing and text comparison utilities to verify file integrity, detect changes, or ensure consistency across your documents and workflows.

Supported Tools & Triggers

Tools
Add Attachments to PDFTool to add file attachments to a PDF document.
Add Image Watermark to PDFTool to add an image watermark to a PDF document.
Add Image Watermark to PDF (Advanced)Tool to add an advanced image watermark to a PDF with precise control over positioning, opacity, scale, quality, and rotation.
Array Add ItemsTool to add items to a JSON array at a specified position (first, last, or specific index).
Create ZIP ArchiveTool to create a ZIP archive from multiple documents.
Apply AI OCR to PDFTool to apply AI-powered OCR to a PDF document with optional preprocessing filters.
Apply OCR to PDF (Standard)Tool to apply standard OCR to a PDF document with optional preprocessing filters.
Decode Base64 StringTool to decode a Base64 string to a file.
Base64 EncodeTool to encode a string to Base64.
Calculate DateTool to calculate a date by adding or subtracting a time interval from a given date.
Check Array Contains ValueTool to check if a value exists within a JSON array.
Check Text Contains ValueTool to check if a text string contains a specific value with configurable comparison rules.
Clean StringTool to clean text by removing control characters, invalid filename characters, and custom character sets.
Clean Up Photo ImageTool to clean up photo images by removing artifacts, correcting orientation, and enhancing quality.
Combine ArraysTool to combine two JSON arrays by matching a key attribute.
Compare TextTool to compare two text strings and determine if they match.
Compare Word DocumentsTool to compare two Microsoft Word or PDF documents and generate a document with tracked changes.
Compress ImageTool to compress an image in JPG or PNG format.
Compress PDFTool to compress a PDF document by optimizing images, removing unused objects, and applying various compression techniques.
Concatenate TextTool to concatenate an array of text values with an optional delimiter.
Array to JSONTool to convert an array to a named JSON object.
Array to XMLTool to convert a JSON array to XML format.
Convert File to PDFTool to convert a file to PDF format.
Convert HTML to ImageTool to convert HTML content to an image.
Convert HTML to PDF (V2)Tool to convert HTML content or a URL to PDF format (V2).
Convert HTML to WordTool to convert HTML content to Word (DOCX) format.
Convert Image to GrayscaleTool to convert an image to grayscale.
Convert Image to PDFTool to convert an image file to PDF format with optional OCR.
Convert JSON to ExcelTool to convert JSON data to Excel format.
Convert JSON to XMLTool to convert JSON data to XML format.
Convert Time ZoneTool to convert a date and time value from one time zone to another using Encodian's time zone conversion API.
Convert XML to JSONTool to convert XML strings to JSON format.
Count Array ItemsTool to count the number of items in a JSON array or object.
Create QR CodeTool to generate a QR code barcode image with customizable size, colors, border, and encoding options.
Format Text CaseTool to format text with various case transformations (uppercase, lowercase, title case, etc.
Hash DataTool to compute a cryptographic hash (MD5, SHA256, etc.
Unzip FileExtracts all files from a ZIP archive and returns their base64-encoded contents.
Get Convert Excel SchemaTool to retrieve the dynamic schema for Excel conversion operations.
Get Convert Word SchemaTool to retrieve the dynamic JSON schema for Word document conversion operations.
Get Convert CAD SchemaTool to retrieve the dynamic schema for CAD file conversion operations.
Get Convert Image to PDF SchemaTool to retrieve the dynamic schema for Convert - Image to PDF operations.
Get Convert PowerPoint SchemaTool to retrieve the dynamic schema for PowerPoint conversion operations.
Get Convert Visio SchemaTool to retrieve the dynamic schema for Visio file conversion.
Get Create Barcode SchemaTool to retrieve the dynamic schema for creating a barcode.
Get Crop Image SchemaTool to retrieve the dynamic schema for the Crop Image action.
Get Dynamic Schema for HTTP RequestTool to retrieve the dynamic schema for the HTTP Request utility based on authentication type.
Get Word Insert Text SchemaTool to retrieve the dynamic schema for Word Insert Text operations.
Get File PropertiesTool to retrieve properties of a file.
Get Operation Status for AIRunPromptTextTool to get the operation status of an AIRunPromptText operation.
Get Operation Status for Encodian Send to FilerTool to get the operation status for an Encodian Send to Filer operation.
Get Operation Status Extract ImageTool to retrieve the operation status of a PDF ExtractImage operation.
Get Operation Status for ExtractTextRegionTool to retrieve the operation status of an ExtractTextRegion operation.
Get Operation Status File OnlyTool to retrieve operation status for file-only operations.
Get Operation Status for Image Extract TextTool to get the operation status of an ImageExtractText operation.
Get Operation Status for Multiple FilesTool to retrieve the operation status of a Word MultipleFiles operation.
Get Operation Status - PDF Split BarcodeTool to retrieve operation status for a PDF split barcode operation.
Get Operation Status for Split DocumentTool to retrieve the operation status of a PDF SplitDocument operation.
Get Sign PDF SchemaTool to retrieve the dynamic schema for PDF signing operations.
Get Subscription StatusTool to retrieve Encodian subscription status for Flowr and Vertr.
Resize ImageTool to resize an image by percentage or dimensions.
Move FileTool to move a file between containers.
Add PDF Header FooterTool to add HTML header and footer to a PDF.
Get PDF MetadataExtract comprehensive metadata and properties from PDF documents.
Watermark PDFTool to apply a text watermark to a PDF.
Read QR Code from DocumentTool to read QR codes from PDF or DOCX documents.
Word - Replace Text With ImageTool to replace text with an image in a Word document.
Validate Email AddressValidates an email address string against a custom regex pattern using Encodian's validation API.
Validate URL AvailabilityTool to validate the availability of a specified URL.
Write Range to ExcelTool to write values to a cell range in an Excel worksheet.

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

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

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.

Install dependencies

pip install composio-langchain langchain-mcp-adapters langchain python-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 is the core agent framework
  • python-dotenv loads environment variables

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

Import dependencies

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()
What's happening:
  • We're importing LangChain's MCP adapter and Composio SDK
  • The dotenv import loads environment variables from your .env file
  • This setup prepares the foundation for connecting LangChain with Encodian functionality through MCP

Initialize Composio client

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")
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 Encodian tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding

Create a Tool Router session

# Create Tool Router session for Encodian
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['encodian']
)

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

Configure the agent with the MCP URL

client = MultiServerMCPClient({
    "encodian-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)
What's happening:
  • We're creating a MultiServerMCPClient that connects to our Encodian MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • get_tools() retrieves all available Encodian tools that the agent can use
  • We're creating a LangChain agent using the GPT-5 model

Set up interactive chat interface

conversation_history = []

print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Encodian 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")
What's happening:
  • We initialize an empty conversation_history list to maintain context across interactions
  • A while loop continuously accepts 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 ainvoke() method with the full conversation history
  • Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully

Run the application

if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • We call the main() function using asyncio.run() to start the application

Complete Code

Here's the complete code to get you started with Encodian and LangChain:

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=['encodian']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "encodian-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 Encodian 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())

Conclusion

You've successfully built a LangChain agent that can interact with Encodian 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.

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FAQ

What are the differences in Tool Router MCP and Encodian MCP?

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

Can I manage the permissions and scopes for Encodian while using Tool Router?

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

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