How to integrate Devolens / Cryptolens MCP with LangChain

This guide walks you through connecting Devolens / Cryptolens to LangChain using the Composio tool router. By the end, you'll have a working Devolens / Cryptolens agent that can view license keys, list your customers, track daily usage, review api logs, and browse products through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Devolens / Cryptolens account through Composio's Devolens / Cryptolens MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

Devolens / Cryptolens logoDevolens / Cryptolens
Api Key

Devolens provides the Cryptolens API for software licensing, license keys, products, customers, entitlements, and usage analytics. Use it to automate license lifecycle management and protect paid software without building a licensing backend.

10 Tools

Introduction

This guide walks you through connecting Devolens / Cryptolens to LangChain using the Composio tool router. By the end, you'll have a working Devolens / Cryptolens agent that can view license keys, list your customers, track daily usage, review api logs, and browse products through natural language commands.

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

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

Also integrate Devolens / Cryptolens with

TL;DR

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

The Devolens / Cryptolens MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Devolens / Cryptolens account. It provides structured and secure access to your software licensing data, so your agent can inspect license keys, review products and templates, find customers and resellers, analyze daily usage, and investigate account activity on your behalf.

  • License key lookup and search: Have your agent retrieve a specific license key with its activation details, or search the keys associated with a product.
  • Product and template review: Let the agent list the products and license templates available in your Cryptolens account.
  • Customer and partner discovery: Direct your agent to find customers, registered license users, and resellers connected to your account.
  • Daily usage analysis: Instruct your agent to review daily usage totals for a product across a selected date range.
  • Activity and message investigation: Have your agent inspect account messages and review web request logs by product, license key, machine, event, or time period.

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 Devolens / Cryptolens 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 Devolens / Cryptolens 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: ['devolens']
    }
);

const url = session.mcp.url;
What's happening:
  • We're creating a Tool Router session that gives your agent access to Devolens / Cryptolens 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 Devolens / Cryptolens tools as needed
8

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "devolens-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 Devolens / Cryptolens MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • getTools() retrieves all available Devolens / Cryptolens 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 Devolens / Cryptolens 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 Devolens / Cryptolens 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: ['devolens']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "devolens-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 Devolens / Cryptolens 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 Devolens / Cryptolens 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 Devolens / Cryptolens action and event your agent gets out of the box.

Get License Key

Retrieve one license key and optional activation metadata by its product ID and key string.

List Customers

Search or list customers visible to the connected Cryptolens account, including reseller-visible customer groups returned by the API.

List Daily Usage Aggregates

Return one page of daily Cryptolens usage aggregates, optionally filtered by product and inclusive date range.

List License Keys

List and search one page of license keys for a Cryptolens product.

List License Templates

Return the license templates available to the connected Cryptolens account.

List License Users

Return registered Cryptolens license users, optionally limited to one customer.

List Messages

Return Cryptolens account messages, optionally filtered by channel or creation time.

List Products

Return the Cryptolens products visible to the connected access token.

List Resellers

Search or list resellers visible to the connected Cryptolens account.

List Web API Logs

Inspect one page of Cryptolens Web API request logs with optional product, license-key, machine, event, and time filters.

FAQ

Frequently asked questions

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

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

Start with Devolens / Cryptolens.It takes 30 seconds.

Managed auth, hosted MCP servers, and every Devolens / Cryptolens tool your agent needs.Free to start.

Start building