How to integrate Encodian MCP with CrewAI

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Introduction

This guide walks you through connecting Encodian to CrewAI 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, move uploaded documents to archive folder through natural language commands.

This guide will help you understand how to give your CrewAI 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.

TL;DR

Here's what you'll learn:
  • Get a Composio API key and configure your Encodian connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Encodian
  • Build a conversational loop where your agent can execute Encodian operations

What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.

Key features include:

  • Agent Roles: Define specialized agents with specific goals and backstories
  • Task Management: Create tasks with clear descriptions and expected outputs
  • Crew Orchestration: Combine agents and tasks into collaborative workflows
  • MCP Integration: Connect to external tools through Model Context Protocol

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
Decode Base64 StringTool to decode a Base64 string to a file.
Base64 EncodeTool to encode a string to Base64.
Compare TextTool to compare two text strings and determine if they match.
Hash DataTool to compute a cryptographic hash (MD5, SHA256, etc.
Unzip FileTool to extract files from an archive.
Get File PropertiesTool to retrieve properties of a file.
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 MetadataTool to extract PDF metadata and properties.
Watermark PDFTool to apply a text watermark to a PDF.
Validate Email AddressTool to validate an email address.
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 Tool Router?

Composio's Tool Router 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 Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router 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, make sure you have:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Encodian connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python

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

bash
pip install composio crewai crewai-tools python-dotenv
What's happening:
  • composio connects your agent to Encodian via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools includes MCP helpers
  • python-dotenv loads environment variables from .env

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_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 with Composio
  • USER_ID scopes the session to your account
  • OPENAI_API_KEY lets CrewAI use your chosen OpenAI model

Import dependencies

python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional import if you plan to adapt tools
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()
What's happening:
  • CrewAI classes define agents and tasks, and run the workflow
  • MCPServerHTTP connects the agent to an MCP endpoint
  • Composio will give you a short lived Encodian MCP URL

Create a Composio Tool Router session for Encodian

python
composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
session = composio.create(
    user_id=os.getenv("USER_ID"),
    toolkits=["encodian"],
)
url = session.mcp.url
What's happening:
  • You create a Encodian only session through Composio
  • Composio returns an MCP HTTP URL that exposes Encodian tools

Configure the LLM

python
llm = LLM(
    model="gpt-5-mini",
    api_key=os.getenv("OPENAI_API_KEY"),
)
What's happening:
  • CrewAI will call this LLM for planning and responses
  • You can swap in a different model if needed

Attach the MCP server and create the agent

python
toolkit_agent = Agent(
    role="Encodian Assistant",
    goal="Help users interact with Encodian through natural language commands",
    backstory=(
        "You are an expert assistant with access to Encodian tools. "
        "You can perform various Encodian operations on behalf of the user."
    ),
    mcps=[
        MCPServerHTTP(
            url=url,
            streamable=True,
            cache_tools_list=True,
            headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
        ),
    ],
    llm=llm,
    verbose=True,
    max_iter=10,
)
What's happening:
  • MCPServerHTTP connects the agent to the Encodian MCP endpoint
  • cache_tools_list saves a tools catalog for faster subsequent runs
  • verbose helps you see what the agent is doing

Add a REPL loop with Task and Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to perform Encodian operations.\n")

conversation_context = ""

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

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

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Based on the conversation history:\n{conversation_context}\n\n"
            f"Current user request: {user_input}\n\n"
            f"Please help the user with their Encodian related request."
        ),
        expected_output="A helpful response addressing the user's request",
        agent=toolkit_agent,
    )

    crew = Crew(
        agents=[toolkit_agent],
        tasks=[task],
        verbose=False,
    )

    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
What's happening:
  • You build a simple chat loop and keep a running context
  • Each user turn becomes a Task handled by the same agent
  • Crew executes the task and returns a response

Run the application

python
if __name__ == "__main__":
    main()
What's happening:
  • Standard Python entry point so you can run python crewai_encodian_agent.py

Complete Code

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

python
# file: crewai_encodian_agent.py
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()

def main():
    # Initialize Composio and create a Encodian session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["encodian"],
    )
    url = session.mcp.url

    # Configure LLM
    llm = LLM(
        model="gpt-5-mini",
        api_key=os.getenv("OPENAI_API_KEY"),
    )

    # Create Encodian assistant agent
    toolkit_agent = Agent(
        role="Encodian Assistant",
        goal="Help users interact with Encodian through natural language commands",
        backstory=(
            "You are an expert assistant with access to Encodian tools. "
            "You can perform various Encodian operations on behalf of the user."
        ),
        mcps=[
            MCPServerHTTP(
                url=url,
                streamable=True,
                cache_tools_list=True,
                headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
            ),
        ],
        llm=llm,
        verbose=True,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Try asking the agent to perform Encodian operations.\n")

    conversation_context = ""

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

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

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Based on the conversation history:\n{conversation_context}\n\n"
                f"Current user request: {user_input}\n\n"
                f"Please help the user with their Encodian related request."
            ),
            expected_output="A helpful response addressing the user's request",
            agent=toolkit_agent,
        )

        crew = Crew(
            agents=[toolkit_agent],
            tasks=[task],
            verbose=False,
        )

        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")

if __name__ == "__main__":
    main()

Conclusion

You now have a CrewAI agent connected to Encodian through Composio's Tool Router. The agent can perform Encodian operations through natural language commands. Next steps:
  • Add role-specific instructions to customize agent behavior
  • Plug in more toolkits for multi-app workflows
  • Chain tasks for complex multi-step operations

How to build Encodian MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Encodian MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Encodian MCP with Claude Agent SDK

Google ADK

Google ADK

Use Encodian MCP with Google ADK

LangChain

LangChain

Use Encodian MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Encodian MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Encodian MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Encodian MCP with LlamaIndex

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 CrewAI?

Yes, you can. CrewAI 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.

Used by agents from

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