How to integrate ReferralRock MCP with Pydantic AI

This guide walks you through connecting ReferralRock to Pydantic AI 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 Pydantic AI 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 Pydantic AI 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 Pydantic AI 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 ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • How to set up your Composio API key and User ID
  • How to create a Composio Tool Router session for ReferralRock
  • How to attach an MCP Server to a Pydantic AI agent
  • How to stream responses and maintain chat history
  • How to build a simple REPL-style chat interface to test your ReferralRock workflows

What is Pydantic AI?

Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications.

Key features include:

  • Type Safety: Built on Pydantic for automatic data validation
  • MCP Support: Native support for Model Context Protocol servers
  • Streaming: Built-in support for streaming responses
  • Async First: Designed for async/await patterns

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 step09 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account with an active 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

bash
pip install composio pydantic-ai python-dotenv

Install the required libraries.

What's happening:

  • composio connects your agent to external SaaS tools like ReferralRock
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your agent to Composio's API
  • USER_ID associates your session with your account for secure tool access
  • OPENAI_API_KEY to access OpenAI LLMs
5

Import dependencies

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()
What's happening:
  • We load environment variables and import required modules
  • Composio manages connections to ReferralRock
  • MCPServerStreamableHTTP connects to the ReferralRock MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant
6

Create a Tool Router Session

python
async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for ReferralRock
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["referralrock"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an 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
7

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
referralrock_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[referralrock_mcp],
    instructions=(
        "You are a ReferralRock assistant. Use ReferralRock tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the ReferralRock endpoint
  • The agent uses GPT-5 to interpret user commands and perform ReferralRock operations
  • The instructions field defines the agent's role and behavior
8

Build the chat interface

python
# Simple REPL with message history
history = []
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to help you with ReferralRock.\n")

while True:
    user_input = input("You: ").strip()
    if user_input.lower() in {"exit", "quit", "bye"}:
        print("\nGoodbye!")
        break
    if not user_input:
        continue

    print("\nAgent is thinking...\n", flush=True)

    async with agent.run_stream(user_input, message_history=history) as stream_result:
        collected_text = ""
        async for chunk in stream_result.stream_output():
            text_piece = None
            if isinstance(chunk, str):
                text_piece = chunk
            elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                text_piece = chunk.delta
            elif hasattr(chunk, "text"):
                text_piece = chunk.text
            if text_piece:
                collected_text += text_piece
        result = stream_result

    print(f"Agent: {collected_text}\n")
    history = result.all_messages()
What's happening:
  • The agent reads input from the terminal and streams its response
  • ReferralRock API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns
9

Run the application

python
if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • The asyncio loop launches the agent and keeps it running until you exit

Complete Code

Here's the complete code to get you started with ReferralRock and Pydantic AI:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()

async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for ReferralRock
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["referralrock"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")

    # Attach the MCP server to a Pydantic AI Agent
    referralrock_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[referralrock_mcp],
        instructions=(
            "You are a ReferralRock assistant. Use ReferralRock tools to help users "
            "with their requests. Ask clarifying questions when needed."
        ),
    )

    # Simple REPL with message history
    history = []
    print("Chat started! Type 'exit' or 'quit' to end.\n")
    print("Try asking the agent to help you with ReferralRock.\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "bye"}:
            print("\nGoodbye!")
            break
        if not user_input:
            continue

        print("\nAgent is thinking...\n", flush=True)

        async with agent.run_stream(user_input, message_history=history) as stream_result:
            collected_text = ""
            async for chunk in stream_result.stream_output():
                text_piece = None
                if isinstance(chunk, str):
                    text_piece = chunk
                elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                    text_piece = chunk.delta
                elif hasattr(chunk, "text"):
                    text_piece = chunk.text
                if text_piece:
                    collected_text += text_piece
            result = stream_result

        print(f"Agent: {collected_text}\n")
        history = result.all_messages()

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You've built a Pydantic AI agent that can interact with ReferralRock through Composio's Tool Router. With this setup, your agent can perform real ReferralRock actions through natural language. You can extend this further by:
  • Adding other toolkits like Gmail, HubSpot, or Salesforce
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + ReferralRock for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.
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

LangChain logo

LangChain

Use ReferralRock MCP with LangChain

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. Pydantic AI 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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Co-Founder, Ingram Technologies