How to integrate ReferralRock MCP with LangChain

This guide walks you through connecting ReferralRock to LangChain using the Composio tool router. By the end, you'll have a working ReferralRock agent that can list all active referral campaigns, add a new member to referral program, show referral stats for this week through natural language commands. This guide will help you understand how to give your LangChain agent real control over a ReferralRock account through Composio's ReferralRock MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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ReferralRock logoReferralRock
Basic

ReferralRock is a referral marketing platform for creating and managing referral programs. It helps businesses drive word-of-mouth growth and increase customer acquisition.

35 Tools

Introduction

This guide walks you through connecting ReferralRock to LangChain using the Composio tool router. By the end, you'll have a working ReferralRock agent that can list all active referral campaigns, add a new member to referral program, show referral stats for this week through natural language commands.

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

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

Also integrate ReferralRock with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

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

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

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 ReferralRock 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 ReferralRock 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: ['referralrock']
    }
);

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

Configure the agent with the MCP URL

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

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

Remove Email from Unsubscribe List

Tool to remove an email address from the unsubscribe list.

Delete Webhook

Tool to delete a webhook subscription.

Delete Members from Program

Tool to delete members from a referral program.

Delete Referral

Tool to delete one or more referrals from a referral program.

Delete Rewards

Tool to delete rewards from members or referrals in a referral program.

Get Email Unsubscribed Status

Tool to check if an email address is unsubscribed from communications.

Get Webhook History for Event

Tool to retrieve webhook history for a specific event.

List Program Members

Tool to list program members with filtering and pagination.

Get Member Statistics

Tool to retrieve comprehensive statistics for a single member from ReferralRock.

Get Payout

Tool to retrieve payout list by ID.

Get Payout Details by ID

Tool to get payout details by ID.

Get Pending Payouts

Tool to get pending payouts for a member or recipient.

Get Payout Transactions

Tool to get payout transaction history for referral program participants.

Get Single Program

Tool to retrieve a single referral program by name.

List Referral Programs

List all referral programs in ReferralRock.

Get Referrals

Tool to list referrals with filtering and pagination options.

Get Single Referral

Tool to retrieve a single referral by email, ID, or external ID.

Get Reward Rules

Tool to get reward rules for a program.

Get Rewards

Tool to list rewards with optional filtering and pagination.

Remove Email from Unsubscribe List

Tool to remove an email address from the unsubscribe list.

Unsubscribe Email Address

Tool to unsubscribe an email address from the ReferralRock mailing list.

Create Webhook Subscription

Tool to create or update a webhook subscription for event notifications.

Create Invite Feed Entry

Tool to create an invite feed entry for automatic invitations.

Create Invite Feed Entries

Tool to create multiple invite feed entries for automatic invites in ReferralRock.

Generate Member Access Token

Tool to generate pre-authenticated member access URLs for sharing and portal experiences.

Generate Member Access URLs

Tool to generate member access URLs for custom share experience or secure portal embedding.

Add new member to program

Tool to create a new member and add them to a referral program.

Remove Members from Program

Tool to remove members from a referral program.

Create Referral Action

Tool to create a referral action for processing recurring rewards.

Remove Referral

Tool to remove referrals from a referral program.

Create New Referral

Tool to create a new referral in ReferralRock based on a member's referral code.

Update Referral Status

Tool to update referral status in ReferralRock.

Update Referral Details

Tool to update referral details in a referral program.

Issue Reward to Member

Tool to issue a reward to a member in the Referral Rock system.

Remove Rewards

Tool to remove rewards from members or referrals of a referral program.

FRAMEWORKS

How to build ReferralRock MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use ReferralRock MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use ReferralRock MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use ReferralRock MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use ReferralRock MCP with Claude Cowork

Codex logo

Codex

Use ReferralRock MCP with Codex

OpenClaw logo

OpenClaw

Use ReferralRock MCP with OpenClaw

Hermes logo

Hermes

Use ReferralRock MCP with Hermes

CLI logo

CLI

Use ReferralRock MCP with CLI

Google ADK logo

Google ADK

Use ReferralRock MCP with Google ADK

Vercel AI SDK logo

Vercel AI SDK

Use ReferralRock MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use ReferralRock MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use ReferralRock MCP with LlamaIndex

CrewAI logo

CrewAI

Use ReferralRock MCP with CrewAI

FAQ

Frequently asked questions

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

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

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A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

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