SIGN UPLOG IN
X (Twitter)LinkedInGitHubDiscordYouTube

How to integrate Splitwise MCP with Pydantic AI

Connect Pydantic AI to Splitwise MCP. Add a new friend using their email, create a dinner expense split equally, and more using natural language, with authentication handled for you.

Get started for freeGet a demo
Splitwise logoSplitwise
Oauth2Api Key

Splitwise helps you split bills and expenses with friends and family. It makes it easy to track shared costs and settle up, so everyone stays on the same page.

27 Tools

Introduction

This guide walks you through connecting Splitwise to Pydantic AI using the Composio tool router. By the end, you'll have a working Splitwise agent that can create and update expenses, manage groups and friends, comment on expenses, restore deleted expenses, and check notifications through natural language commands.

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

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

For exact tool slugs and parameter tables, see the tool catalog in the Composio docs.

Also integrate Splitwise with

Claude CodeClaude CoworkOpenAI Agents SDKClaude Agent SDKCodexOpenClawHermesAtomic AgentGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAIAutoGen

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 Splitwise
  • 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 Splitwise 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 Splitwise MCP server, and what's possible with it?

The Splitwise MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Splitwise account. It provides structured and secure access to your expenses and group data, so your agent can perform actions like creating expenses, adding friends, retrieving categories, and managing your account on your behalf.

  • Expense tracking and creation: Quickly have your agent record new expenses, split bills, or log payments—either between you and friends or within groups.
  • Friend and contact management: Easily add new friends with their email and name, or remove existing friends to keep your network current.
  • Group info and collaboration: Retrieve details about any group you belong to, making it simple to manage shared costs and stay organized with your housemates, travel buddies, or teams.
  • Expense category and currency lookup: Ask the agent to fetch available expense categories or supported currencies, helping you record transactions accurately and consistently.
  • Account and profile insights: Let your agent pull your current user details so you can quickly review account information or verify profile data as needed.

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 Splitwise
  • 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 Splitwise
  • MCPServerStreamableHTTP connects to the Splitwise 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 Splitwise
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["splitwise"],
    )
    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 Splitwise 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
splitwise_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[splitwise_mcp],
    instructions=(
        "You are a Splitwise assistant. Use Splitwise tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Splitwise endpoint
  • The agent uses GPT-5 to interpret user commands and perform Splitwise 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 Splitwise.\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
  • Splitwise 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 Splitwise 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 Splitwise
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["splitwise"],
    )
    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
    splitwise_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[splitwise_mcp],
        instructions=(
            "You are a Splitwise assistant. Use Splitwise 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 Splitwise.\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 Splitwise through Composio's Tool Router. With this setup, your agent can perform real Splitwise 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 + Splitwise 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 Splitwise action and event your agent gets out of the box.

Add Friend

Tool to add a new friend to Splitwise.

Add User to Group

Tool to add a user to a group.

Create Comment

Tool to create a comment on a specific expense.

Create Expense

Creates a Splitwise expense for a group or between users to record a bill or payment.

Create Friends

Tool to add multiple friends at once to Splitwise.

Create Group

Tool to create a new group in Splitwise.

Delete Comment

Tool to delete a comment by its ID.

Delete Expense

Deletes an existing expense by ID; Splitwise supports restoring deleted expenses.

Delete Friend

Tool to delete an existing friend by ID.

Delete Group

Deletes a group by ID and destroys its associated records, including expenses.

Get Categories

Tool to retrieve expense categories.

Get Comments

Tool to retrieve all comments associated with a specific expense.

Get Currencies

Tool to retrieve a list of supported currencies.

Get Current User

Tool to retrieve information about the current authenticated user.

Get Expense

Tool to retrieve detailed information about a specific expense by ID.

Get Expenses

Lists the current user's Splitwise expenses with optional date, group, and friend filters.

Get Friend Details

Tool to retrieve detailed information about a specific friend.

Get Friends

Tool to list current user's friends on Splitwise.

Get Group Details

Retrieves details for a specific group, including members, balances, original and simplified debts, avatar URLs, and settings.

Get Groups

Retrieves all groups the authenticated user belongs to, including group details, members, balances, and debt information.

Get Notifications

Tool to retrieve recent activity notifications from the user's Splitwise account.

Get User Information

Retrieves basic profile information about any Splitwise user by their ID.

Remove User from Group

Tool to remove a user from a group.

Restore Deleted Expense

Restores a previously deleted expense by ID.

Restore Deleted Group

Restores a previously deleted group by ID.

Update Expense

Updates an existing Splitwise expense's details, such as cost, description, or participant shares; supplying participant shares overwrites all existing shares.

Update User

Tool to update user account details including name, email, password, and preferences.

FRAMEWORKS

How to build Splitwise MCP Agent with another framework

Claude Code logo

Claude Code

Use Splitwise MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Splitwise MCP with Claude Cowork

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Splitwise MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Splitwise MCP with Claude Agent SDK

Codex logo

Codex

Use Splitwise MCP with Codex

OpenClaw logo

OpenClaw

Use Splitwise MCP with OpenClaw

Hermes logo

Hermes

Use Splitwise MCP with Hermes

Atomic Agent logo

Atomic Agent

Use Splitwise MCP with Atomic Agent

Google ADK logo

Google ADK

Use Splitwise MCP with Google ADK

LangChain logo

LangChain

Use Splitwise MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Splitwise MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Splitwise MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Splitwise MCP with LlamaIndex

CrewAI logo

CrewAI

Use Splitwise MCP with CrewAI

AutoGen logo

AutoGen

Use Splitwise MCP with AutoGen

FAQ

Frequently asked questions

Start with Splitwise.It takes 30 seconds.

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

Start building