How to integrate Persona MCP with LangChain

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Introduction

This guide walks you through connecting Persona to LangChain using the Composio tool router. By the end, you'll have a working Persona agent that can get all pending verification cases, trigger a new kyc verification for user, list users who failed identity checks through natural language commands.

This guide will help you understand how to give your LangChain agent real control over a Persona account through Composio's Persona 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 and set up your OpenAI and Composio API keys
  • Connect your Persona project to Composio
  • Create a Tool Router MCP session for Persona
  • Initialize an MCP client and retrieve Persona tools
  • Build a LangChain agent that can interact with Persona
  • 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 Persona MCP server, and what's possible with it?

The Persona MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Persona account. It provides structured and secure access so your agent can perform Persona operations on your behalf.

Supported Tools & Triggers

Tools
Add Tag to AccountTool to add a tag to an Account in Persona.
Archive Browser Fingerprint List ItemTool to archive a browser fingerprint list item in Persona.
Archive Country List ItemTool to archive a Country List Item by ID.
Archive a Geolocation List ItemTool to archive a geolocation list item from Persona.
Archive Government ID Number List ItemTool to archive a Government ID Number List Item.
Archive a Name List ItemTool to archive a name list item in Persona.
Archive a webhookTool to archive a Persona webhook by its ID.
Archive Email Address List ItemTool to archive an Email Address List Item in Persona.
Archive IP Address List ItemTool to archive an IP address list item in Persona.
Archive Phone Number List ItemTool to archive a phone number list item in Persona.
Archive String List ItemTool to archive a String List Item in Persona.
Clone WebhookTool to clone an existing Persona webhook.
Consolidate AccountsTool to consolidate multiple source accounts into a single destination account.
Create an AccountTool to create an account in Persona.
Create IP Address List ItemTool to create an IP Address List Item in Persona.
Create Country List ItemTool to create a country list item in Persona.
Create Generic DocumentTool to create a generic document in Persona.
Create Email Address List ItemTool to create an email address list item in Persona.
Create Government ID Number List ItemTool to create a new government ID number list item in Persona.
Create Name List ItemTool to create a new name list item in Persona.
Create Phone Number List ItemTool to create a phone number list item in Persona.
Create String List ItemTool to create a String List Item in Persona.
Create WebhookTool to create a new webhook in Persona.
Disable WebhookTool to disable a webhook in Persona.
Enable WebhookTool to enable a webhook in Persona.
Expire Inquiry SessionsTool to expire all inquiry sessions for specified inquiry IDs.
Import Email Address ListsTool to import email addresses into a list from a CSV file.
Import IP Address ListsTool to import IP address lists into Persona.
Import Name ListsTool to import name lists to Persona.
Import Phone Number ListsTool to import phone number lists into Persona.
List All AccountsTool to list all accounts in Persona.
List All API LogsTool to list all API logs in Persona.
List All CasesTool to list all cases in Persona.
List All DevicesTool to list all devices filtered by inquiry session ID.
List all EventsTool to list all events from Persona.
List all ImportersTool to list all importers in Persona.
List All InquiriesTool to list all inquiries in Persona.
List All Inquiry SessionsTool to list all inquiry sessions in Persona.
List All ListsTool to list all lists in Persona.
List All Rate LimitsTool to list all rate limits in Persona.
List All ReportsTool to list all reports in Persona.
List All TransactionsTool to list all transactions in Persona.
List All WebhooksTool to list all webhooks in Persona.
List all Workflow RunsTool to list all workflow runs in Persona.
Redact an AccountTool to permanently redact an account in Persona.
Remove Account TagTool to remove a tag from a Persona Account.
Retrieve a Country List ItemTool to retrieve a country list item by ID in Persona.
Retrieve a Geolocation List ItemTool to retrieve a geolocation list item from Persona.
Retrieve an AccountTool to retrieve an account in Persona.
Retrieve a Name List ItemTool to retrieve a Name List Item in Persona.
Retrieve an EventTool to retrieve an event in Persona.
Retrieve an ImporterTool to retrieve a specific importer in Persona.
Retrieve IP Address List ItemTool to retrieve an IP Address List Item in Persona.
Retrieve an API LogTool to retrieve an API log in Persona.
Retrieve a String List ItemTool to retrieve a string list item by ID in Persona.
Retrieve a WebhookTool to retrieve a webhook by its ID.
Retrieve Browser Fingerprint List ItemTool to retrieve a browser fingerprint list item in Persona.
Retrieve a DocumentTool to retrieve a document from Persona.
Retrieve Generic DocumentTool to retrieve a generic document in Persona.
Retrieve Email Address List ItemTool to retrieve an Email Address List Item in Persona.
Retrieve Government ID Number List ItemTool to retrieve a Government ID Number List Item in Persona.
Retrieve Phone Number List ItemTool to retrieve a phone number list item in Persona.
Rotate Webhook SecretTool to rotate a webhook's secret in Persona.
Search AccountsTool to search accounts in Persona using flexible query criteria.
Search CasesTool to search cases in Persona using advanced query filters with boolean logic.
Set Tags on AccountTool to set tags on a Persona Account.
Update an AccountTool to update an account in Persona.
Update a WebhookTool to update a webhook in Persona.
Update Generic DocumentTool to update a generic document in Persona.

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 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 Persona 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 Persona tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding

Create a Tool Router session

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

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

Configure the agent with the MCP URL

client = MultiServerMCPClient({
    "persona-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 Persona MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • get_tools() retrieves all available Persona 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 Persona 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 Persona 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=['persona']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "persona-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 Persona 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 Persona 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 Persona MCP Agent with another framework

FAQ

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

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

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

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

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