How to integrate Beaconchain MCP with LangChain

This guide walks you through connecting Beaconchain to LangChain using the Composio tool router. By the end, you'll have a working Beaconchain agent that can check if your ethereum node is syncing, get health status of the beacon chain node, fetch details for validator id 12345 through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Beaconchain account through Composio's Beaconchain MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

Beaconchain logoBeaconchain
Api Key

Beaconchain is a real-time analytics platform for Ethereum 2.0's Beacon Chain. It provides detailed insights into validators, blocks, and overall network performance.

37 Tools

Introduction

This guide walks you through connecting Beaconchain to LangChain using the Composio tool router. By the end, you'll have a working Beaconchain agent that can check if your ethereum node is syncing, get health status of the beacon chain node, fetch details for validator id 12345 through natural language commands.

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

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

Also integrate Beaconchain with

TL;DR

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

The Beaconchain MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Beaconchain account. It provides structured and secure access to Ethereum 2.0 Beacon Chain analytics, so your agent can check validator status, monitor node health, analyze network performance, and surface real-time blockchain insights on your behalf.

  • Validator information lookup: Instantly retrieve in-depth details about any specific Ethereum 2.0 validator, including performance, status, and rewards.
  • Node health monitoring: Let your agent check the real-time health status of your node, including readiness, syncing state, and error conditions.
  • Network performance insights: Surface up-to-date statistics on the overall Beacon Chain network, empowering you to make informed decisions.
  • Automated health alerts: Have your agent proactively monitor node status and notify you if any issues or anomalies arise.

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 Beaconchain 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 Beaconchain 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: ['beaconchain']
    }
);

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

Configure the agent with the MCP URL

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

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

Get Chart

Retrieve chart visualizations from beaconcha.

Get Epoch

Retrieve aggregate metrics and status for a beacon chain epoch.

Get ETH1 Deposits by Transaction Hash

Retrieve all beacon chain validator deposit events associated with a specific execution-layer transaction hash.

Get ETH.Store Daily Aggregates

Retrieve ETH.

Get ERC-20 Token Balances

Retrieve a paginated list of ERC-20 token balances for a specific Ethereum address.

Get Execution Block

Retrieve one or more execution-layer blocks by block number from the Ethereum Beacon Chain.

Get Execution Produced Blocks

Retrieve execution-layer blocks attributed to one or more producers.

Get Latest State

Retrieve the latest known Ethereum Beacon Chain network state.

Get Network Performance

Retrieve aggregated network performance metrics for the Ethereum Beacon Chain.

Get Explorer Health

Check the health status of the beaconcha.

Get Validator Queues

Retrieve current queue metrics for Ethereum Beacon Chain validators.

Get Rocket Pool Validator

Retrieve Rocket Pool-specific metadata for validators including minipool status, node fee, smoothing pool status, and RPL stake metrics.

Get Slot

Retrieve detailed information about an Ethereum Beacon Chain slot.

Get Slot Attestations

Retrieve all attestations included in the beacon block for a specific slot.

Get Slot Attester Slashings

Retrieve all attester slashing operations included in the beacon block for a specific slot.

Get Slot Proposer Slashings

Retrieve all proposer slashing operations included in the beacon block for a specific slot.

Get Slot Voluntary Exits

Retrieve all voluntary exit operations included in the beacon block for a specific slot.

Get Sync Committee

Retrieve the sync committee membership for a given sync period.

Get Validator

Retrieve detailed information about an Ethereum Beacon Chain validator.

Get Validator Attestation Efficiency

Retrieve normalized attestation inclusion effectiveness for one or more validators.

Get Validator Attestations

Retrieve attestations observed for one or more validators within a bounded epoch window.

Get Validator Balance History

Retrieve per-epoch balance history for one or more Ethereum Beacon Chain validators.

Get Validator BLS Changes

Retrieve on-chain BLS-to-execution credential change messages (EIP-4881) for validators.

Get Validator Consensus Rewards

Retrieve consensus-layer rewards for one or more validators over multiple lookback windows.

Get Validator Daily Stats

Retrieve per-day statistics for a single Ethereum Beacon Chain validator by index.

Get Validator Deposits

Retrieve execution-layer deposit events for one or more validators.

Get Validator Execution Rewards

Retrieve execution-layer rewards (priority fees and MEV payments) for one or more validators.

Get Validator Income History

Retrieve a per-epoch income breakdown for one or more validators.

Get Validator Leaderboard

Retrieve the current top 100 validators ranked by 7-day consensus-layer rewards.

Get Validator Proposals

Retrieve beacon chain blocks proposed by one or more validators within a bounded epoch window.

Get Validators by Deposit Address

Retrieve validators that have made deposits from a specific execution-layer address.

Get Validators by Withdrawal Credentials

Retrieve validators whose withdrawal credentials match the provided value or execution-layer address.

Get Validators Proposal Luck

Retrieve proposal luck statistics for one or more Ethereum Beacon Chain validators.

Get Validators Queue

Retrieve current queue metrics for validators on the Ethereum Beacon Chain.

Get Validator Withdrawals

Retrieve withdrawal operations attributed to one or more validators within a bounded epoch window.

Post Validators

Retrieve validator information using a JSON request body for multiple validators.

Resolve ENS Name or Address

Resolve ENS (Ethereum Name Service) names to addresses and vice versa.

FAQ

Frequently asked questions

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

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

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