How to integrate Beaconchain MCP with LangChain

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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.

Supported Tools & Triggers

Tools
Get ChartRetrieve chart visualizations from beaconcha.
Get EpochRetrieve aggregate metrics and status for a beacon chain epoch.
Get ETH1 Deposits by Transaction HashRetrieve all beacon chain validator deposit events associated with a specific execution-layer transaction hash.
Get ETH.Store Daily AggregatesRetrieve ETH.
Get ERC-20 Token BalancesRetrieve a paginated list of ERC-20 token balances for a specific Ethereum address.
Get Execution BlockRetrieve one or more execution-layer blocks by block number from the Ethereum Beacon Chain.
Get Execution Produced BlocksRetrieve execution-layer blocks attributed to one or more producers.
Get Latest StateRetrieve the latest known Ethereum Beacon Chain network state.
Get Network PerformanceRetrieve aggregated network performance metrics for the Ethereum Beacon Chain.
Get Explorer HealthCheck the health status of the beaconcha.
Get Validator QueuesRetrieve current queue metrics for Ethereum Beacon Chain validators.
Get Rocket Pool ValidatorRetrieve Rocket Pool-specific metadata for validators including minipool status, node fee, smoothing pool status, and RPL stake metrics.
Get SlotRetrieve detailed information about an Ethereum Beacon Chain slot.
Get Slot AttestationsRetrieve all attestations included in the beacon block for a specific slot.
Get Slot Attester SlashingsRetrieve all attester slashing operations included in the beacon block for a specific slot.
Get Slot Proposer SlashingsRetrieve all proposer slashing operations included in the beacon block for a specific slot.
Get Slot Voluntary ExitsRetrieve all voluntary exit operations included in the beacon block for a specific slot.
Get Sync CommitteeRetrieve the sync committee membership for a given sync period.
Get ValidatorRetrieve detailed information about an Ethereum Beacon Chain validator.
Get Validator Attestation EfficiencyRetrieve normalized attestation inclusion effectiveness for one or more validators.
Get Validator AttestationsRetrieve attestations observed for one or more validators within a bounded epoch window.
Get Validator Balance HistoryRetrieve per-epoch balance history for one or more Ethereum Beacon Chain validators.
Get Validator BLS ChangesRetrieve on-chain BLS-to-execution credential change messages (EIP-4881) for validators.
Get Validator Consensus RewardsRetrieve consensus-layer rewards for one or more validators over multiple lookback windows.
Get Validator Daily StatsRetrieve per-day statistics for a single Ethereum Beacon Chain validator by index.
Get Validator DepositsRetrieve execution-layer deposit events for one or more validators.
Get Validator Execution RewardsRetrieve execution-layer rewards (priority fees and MEV payments) for one or more validators.
Get Validator Income HistoryRetrieve a per-epoch income breakdown for one or more validators.
Get Validator LeaderboardRetrieve the current top 100 validators ranked by 7-day consensus-layer rewards.
Get Validator ProposalsRetrieve beacon chain blocks proposed by one or more validators within a bounded epoch window.
Get Validators by Deposit AddressRetrieve validators that have made deposits from a specific execution-layer address.
Get Validators by Withdrawal CredentialsRetrieve validators whose withdrawal credentials match the provided value or execution-layer address.
Get Validators Proposal LuckRetrieve proposal luck statistics for one or more Ethereum Beacon Chain validators.
Get Validators QueueRetrieve current queue metrics for validators on the Ethereum Beacon Chain.
Get Validator WithdrawalsRetrieve withdrawal operations attributed to one or more validators within a bounded epoch window.
Post ValidatorsRetrieve validator information using a JSON request body for multiple validators.
Resolve ENS Name or AddressResolve ENS (Ethereum Name Service) names to addresses and vice versa.

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

Create a Tool Router session

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

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

Configure the agent with the MCP URL

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

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "beaconchain-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 Beaconchain 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 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.

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FAQ

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

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.

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 Beaconchain tools.

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

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.

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 Beaconchain data and credentials are handled as safely as possible.

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