# How to integrate Splitwise MCP with LlamaIndex

```json
{
  "title": "How to integrate Splitwise MCP with LlamaIndex",
  "toolkit": "Splitwise",
  "toolkit_slug": "splitwise",
  "framework": "LlamaIndex",
  "framework_slug": "llama-index",
  "url": "https://composio.dev/toolkits/splitwise/framework/llama-index",
  "markdown_url": "https://composio.dev/toolkits/splitwise/framework/llama-index.md",
  "updated_at": "2026-05-12T10:26:49.209Z"
}
```

## Introduction

This guide walks you through connecting Splitwise to LlamaIndex using the Composio tool router. By the end, you'll have a working Splitwise agent that can add a new friend using their email, create a dinner expense split equally, list all groups i'm part of through natural language commands.
This guide will help you understand how to give your LlamaIndex 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.

## Also integrate Splitwise with

- [OpenAI Agents SDK](https://composio.dev/toolkits/splitwise/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/splitwise/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/splitwise/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/splitwise/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/splitwise/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/splitwise/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/splitwise/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/splitwise/framework/cli)
- [Google ADK](https://composio.dev/toolkits/splitwise/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/splitwise/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/splitwise/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/splitwise/framework/mastra-ai)
- [CrewAI](https://composio.dev/toolkits/splitwise/framework/crew-ai)

## TL;DR

Here's what you'll learn:
- Set your OpenAI and Composio API keys
- Install LlamaIndex and Composio packages
- Create a Composio Tool Router session for Splitwise
- Connect LlamaIndex to the Splitwise MCP server
- Build a Splitwise-powered agent using LlamaIndex
- Interact with Splitwise through natural language

## What is LlamaIndex?

LlamaIndex is a data framework for building LLM applications. It provides tools for connecting LLMs to external data sources and services through agents and tools.
Key features include:
- ReAct Agent: Reasoning and acting pattern for tool-using agents
- MCP Tools: Native support for Model Context Protocol
- Context Management: Maintain conversation context across interactions
- Async Support: Built 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.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `SPLITWISE_ADD_FRIEND` | Add Friend | Tool to add a new friend to Splitwise. Use when you have the friend's email and name details ready. |
| `SPLITWISE_ADD_USER_TO_GROUP` | Add User to Group | Tool to add a user to a group. Use when you need to add an existing Splitwise user to a specific group. Note: 200 OK does not indicate success; always check the response 'success' field. |
| `SPLITWISE_CREATE_COMMENT` | Create Comment | Tool to create a comment on a specific expense. Use when you need to add a comment or note to an existing expense. |
| `SPLITWISE_CREATE_EXPENSE` | Create Expense | Tool to create a new Splitwise expense. Use when you need to record a payment or bill in a group or between users. Provide exactly one of split_equally or users for shares — supplying both or neither causes a validation error and no expense is created. |
| `SPLITWISE_CREATE_FRIENDS` | Create Friends | Tool to add multiple friends at once to Splitwise. Use when you need to add several friends in a single operation. |
| `SPLITWISE_CREATE_GROUP` | Create Group | Tool to create a new group in Splitwise. Use when you need to create a group for tracking shared expenses. The current user is automatically added to the group. You can optionally add other members during creation. |
| `SPLITWISE_DELETE_COMMENT` | Delete Comment | Tool to delete a comment by its ID. Use after confirming you have a valid comment ID. |
| `SPLITWISE_DELETE_EXPENSE` | Delete Expense | Tool to delete an existing expense by its ID. Deletion is irreversible — no undelete capability exists. Use after confirming you have the correct expense ID. Inspect the response's `success` and `error` fields to verify deletion succeeded; failures (e.g., user lacks owner/participant permissions) are surfaced there. |
| `SPLITWISE_DELETE_FRIEND` | Delete Friend | Tool to delete an existing friend by ID. Use when you need to remove a friend relationship by its user ID. Call after confirming the correct friend ID. |
| `SPLITWISE_DELETE_GROUP` | Delete Group | Tool to delete a group and all associated records by its ID. Use when you need to permanently remove a group and its expenses. Call after confirming the correct group ID. |
| `SPLITWISE_GET_CATEGORIES` | Get Categories | Tool to retrieve expense categories. Use when you need to list available categories before creating an expense. |
| `SPLITWISE_GET_COMMENTS` | Get Comments | Tool to retrieve all comments associated with a specific expense. Use when you need to view comments on an expense, including both system-generated updates and user-authored messages. |
| `SPLITWISE_GET_CURRENCIES` | Get Currencies | Tool to retrieve a list of supported currencies. Use when you need to display or validate currency options. |
| `SPLITWISE_GET_CURRENT_USER` | Get Current User | Tool to retrieve information about the current authenticated user. Use when you need profile details of the logged-in user. |
| `SPLITWISE_GET_EXPENSE` | Get Expense | Tool to retrieve detailed information about a specific expense by ID. Use when you need to view expense details including participants, shares, and repayments. |
| `SPLITWISE_GET_EXPENSES` | Get Expenses | Tool to list the current user's expenses from Splitwise account. Use when you need to view expenses with optional filters like date ranges, groups, or friends. |
| `SPLITWISE_GET_FRIEND` | Get Friend Details | Tool to retrieve detailed information about a specific friend. Use when you need to get profile details and balance information for a friend by their user ID. |
| `SPLITWISE_GET_FRIENDS` | Get Friends | Tool to list current user's friends on Splitwise. Use when you need to view all friends, their balances, and shared groups. |
| `SPLITWISE_GET_GROUP` | Get Group Details | Tool to retrieve detailed information about a specific group. Returns full group details including members, balances, debts (both original and simplified), avatar URLs, and group settings. Use this when you need comprehensive information about a particular group, such as viewing who owes what to whom. Use group ID of 0 to get non-group expenses. |
| `SPLITWISE_GET_GROUPS` | Get Groups | Retrieves all groups the authenticated user belongs to, including group details, members, balances, and debt information. Returns a 'groups' array with no server-side filtering; all name- or ID-based filtering must be done client-side on the full response. Group names may share similar strings or differ in case/whitespace — normalize when matching and prefer group_id once identified. The groups array may be empty if the user belongs to no groups. |
| `SPLITWISE_GET_NOTIFICATIONS` | Get Notifications | Tool to retrieve recent activity notifications from the user's Splitwise account. Returns notifications with HTML content suitable for display, with the most recent items first. Use when you need to view recent account activity or updates. |
| `SPLITWISE_GET_USER` | Get User Information | Retrieves basic profile information about any Splitwise user by their ID. Returns the user's name, email, registration status, and profile picture. This endpoint only returns public user information. For the authenticated user's full profile (including notifications, currency preferences, and locale settings), use get_current_user instead. |
| `SPLITWISE_REMOVE_USER_FROM_GROUP` | Remove User from Group | Tool to remove a user from a group. Use when you need to remove a user from a specific group. Note: User must have a zero balance in the group for removal to succeed. 200 OK does not indicate success; always check the response 'success' field. |
| `SPLITWISE_UNDELETE_EXPENSE` | Restore Deleted Expense | Tool to restore a previously deleted expense and its associated records. Use when you need to recover an expense that was deleted. Call after confirming the correct expense ID. Not a guaranteed undo mechanism — treat deletion as high-impact and verify restoration completeness afterward. |
| `SPLITWISE_UNDELETE_GROUP` | Restore Deleted Group | Tool to restore a previously deleted group and all its associated records. Use when you need to recover a group that was deleted. Call after confirming the correct group ID. |
| `SPLITWISE_UPDATE_EXPENSE` | Update Expense | Tool to update an existing Splitwise expense. Use when you need to modify expense details such as cost, description, or participant shares. Only include fields you want to change. Note that a 200 OK response does not guarantee success - check that the errors object is empty. |
| `SPLITWISE_UPDATE_USER` | Update User | Tool to update user account details including name, email, password, and preferences. Use when you need to modify the current user's profile information. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Splitwise MCP server is an implementation of the Model Context Protocol that connects your AI agent to Splitwise. It provides structured and secure access so your agent can perform Splitwise operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. Prerequisites

Before you begin, make sure you have:
- Python 3.8/Node 16 or higher installed
- A Composio account with the API key
- An OpenAI API key
- A Splitwise account and project
- Basic familiarity with async Python/Typescript

### 1. Getting API Keys for OpenAI, Composio, and Splitwise

No description provided.

### 2. Installing dependencies

No description provided.
```python
pip install composio-llamaindex llama-index llama-index-llms-openai llama-index-tools-mcp python-dotenv
```

```typescript
npm install @composio/llamaindex @llamaindex/openai @llamaindex/tools @llamaindex/workflow dotenv
```

### 3. Set environment variables

Create a .env file in your project root:
These credentials will be used to:
- Authenticate with OpenAI's GPT-5 model
- Connect to Composio's Tool Router
- Identify your Composio user session for Splitwise access
```bash
OPENAI_API_KEY=your-openai-api-key
COMPOSIO_API_KEY=your-composio-api-key
COMPOSIO_USER_ID=your-user-id
```

### 4. Import modules

No description provided.
```python
import asyncio
import os
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()
```

```typescript
import "dotenv/config";
import readline from "node:readline/promises";
import { stdin as input, stdout as output } from "node:process";

import { Composio } from "@composio/core";

import { mcp } from "@llamaindex/tools";
import { agent as createAgent } from "@llamaindex/workflow";
import { openai } from "@llamaindex/openai";

dotenv.config();
```

### 5. Load environment variables and initialize Composio

No description provided.
```python
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set in the environment")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment")
```

```typescript
const OPENAI_API_KEY = process.env.OPENAI_API_KEY;
const COMPOSIO_API_KEY = process.env.COMPOSIO_API_KEY;
const COMPOSIO_USER_ID = process.env.COMPOSIO_USER_ID;

if (!OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set");
if (!COMPOSIO_API_KEY) throw new Error("COMPOSIO_API_KEY is not set");
if (!COMPOSIO_USER_ID) throw new Error("COMPOSIO_USER_ID is not set");
```

### 6. Create a Tool Router session and build the agent function

What's happening here:
- We create a Composio client using your API key and configure it with the LlamaIndex provider
- We then create a tool router MCP session for your user, specifying the toolkits we want to use (in this case, splitwise)
- The session returns an MCP HTTP endpoint URL that acts as a gateway to all your configured tools
- LlamaIndex will connect to this endpoint to dynamically discover and use the available Splitwise tools.
- The MCP tools are mapped to LlamaIndex-compatible tools and plug them into the Agent.
```python
async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["splitwise"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")

    description = "An agent that uses Composio Tool Router MCP tools to perform Splitwise actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Splitwise actions.
    """
    return ReActAgent(tools=tools, llm=llm, description=description, system_prompt=system_prompt, verbose=True)
```

```typescript
async function buildAgent() {

  console.log(`Initializing Composio client...${COMPOSIO_USER_ID!}...`);
  console.log(`COMPOSIO_USER_ID: ${COMPOSIO_USER_ID!}...`);

  const composio = new Composio({
    apiKey: COMPOSIO_API_KEY,
    provider: new LlamaindexProvider(),
  });

  const session = await composio.create(
    COMPOSIO_USER_ID!,
    {
      toolkits: ["splitwise"],
    },
  );

  const mcpUrl = session.mcp.url;
  console.log(`Composio Tool Router MCP URL: ${mcpUrl}`);

  const server = mcp({
    url: mcpUrl,
    clientName: "composio_tool_router_with_llamaindex",
    requestInit: {
      headers: {
        "x-api-key": COMPOSIO_API_KEY!,
      },
    },
    // verbose: true,
  });

  const tools = await server.tools();

  const llm = openai({ apiKey: OPENAI_API_KEY, model: "gpt-5" });

  const agent = createAgent({
    name: "composio_tool_router_with_llamaindex",
        description : "An agent that uses Composio Tool Router MCP tools to perform actions.",
    systemPrompt:
      "You are a helpful assistant connected to Composio Tool Router."+
"Use the available tools to answer user queries and perform Splitwise actions." ,
    llm,
    tools,
  });

  return agent;
}
```

### 7. Create an interactive chat loop

No description provided.
```python
async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")
```

```typescript
async function chatLoop(agent: ReturnType<typeof createAgent>) {
  const rl = readline.createInterface({ input, output });

  console.log("Type 'quit' or 'exit' to stop.");

  while (true) {
    let userInput: string;

    try {
      userInput = (await rl.question("\nYou: ")).trim();
    } catch {
      console.log("\nAgent: Bye!");
      break;
    }

    if (!userInput) {
      continue;
    }

    const lower = userInput.toLowerCase();
    if (lower === "quit" || lower === "exit") {
      console.log("Agent: Bye!");
      break;
    }

    try {
      process.stdout.write("Agent: ");

      const stream = agent.runStream(userInput);
      let finalResult: any = null;

      for await (const event of stream) {
        // The event.data contains the streamed content
        const data: any = event.data;

        // Check for streaming delta content
        if (data?.delta) {
          process.stdout.write(data.delta);
        }

        // Store final result for fallback
        if (data?.result || data?.message) {
          finalResult = data;
        }
      }

      // If no streaming happened, show the final result
      if (finalResult) {
        const answer =
          finalResult.result ??
          finalResult.message?.content ??
          finalResult.message ??
          "";
        if (answer && typeof answer === "string" && !answer.includes("[object")) {
          process.stdout.write(answer);
        }
      }

      console.log(); // New line after streaming completes
    } catch (err: any) {
      console.error("\nAgent error:", err?.message ?? err);
    }
  }

  rl.close();
}
```

### 8. Define the main entry point

What's happening here:
- We're orchestrating the entire application flow
- The agent gets built with proper error handling
- Then we kick off the interactive chat loop so you can start talking to Splitwise
```python
async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")
```

```typescript
async function main() {
  try {
    const agent = await buildAgent();
    await chatLoop(agent);
  } catch (err) {
    console.error("Failed to start agent:", err);
    process.exit(1);
  }
}

main();
```

### 9. Run the agent

When prompted, authenticate and authorise your agent with Splitwise, then start asking questions.
```bash
python llamaindex_agent.py
```

```typescript
npx ts-node llamaindex-agent.ts
```

## Complete Code

```python
import asyncio
import os
import signal
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")

async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["splitwise"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")
    description = "An agent that uses Composio Tool Router MCP tools to perform Splitwise actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Splitwise actions.
    """
    return ReActAgent(
        tools=tools,
        llm=llm,
        description=description,
        system_prompt=system_prompt,
        verbose=True,
    );

async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")

async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")
```

```typescript
import "dotenv/config";
import readline from "node:readline/promises";
import { stdin as input, stdout as output } from "node:process";

import { Composio } from "@composio/core";
import { LlamaindexProvider } from "@composio/llamaindex";

import { mcp } from "@llamaindex/tools";
import { agent as createAgent } from "@llamaindex/workflow";
import { openai } from "@llamaindex/openai";

dotenv.config();

const OPENAI_API_KEY = process.env.OPENAI_API_KEY;
const COMPOSIO_API_KEY = process.env.COMPOSIO_API_KEY;
const COMPOSIO_USER_ID = process.env.COMPOSIO_USER_ID;

if (!OPENAI_API_KEY) {
    throw new Error("OPENAI_API_KEY is not set in the environment");
  }
if (!COMPOSIO_API_KEY) {
    throw new Error("COMPOSIO_API_KEY is not set in the environment");
  }
if (!COMPOSIO_USER_ID) {
    throw new Error("COMPOSIO_USER_ID is not set in the environment");
  }

async function buildAgent() {

  console.log(`Initializing Composio client...${COMPOSIO_USER_ID!}...`);
  console.log(`COMPOSIO_USER_ID: ${COMPOSIO_USER_ID!}...`);

  const composio = new Composio({
    apiKey: COMPOSIO_API_KEY,
    provider: new LlamaindexProvider(),
  });

  const session = await composio.create(
    COMPOSIO_USER_ID!,
    {
      toolkits: ["splitwise"],
    },
  );

  const mcpUrl = session.mcp.url;
  console.log(`Composio Tool Router MCP URL: ${mcpUrl}`);

  const server = mcp({
    url: mcpUrl,
    clientName: "composio_tool_router_with_llamaindex",
    requestInit: {
      headers: {
        "x-api-key": COMPOSIO_API_KEY!,
      },
    },
    // verbose: true,
  });

  const tools = await server.tools();

  const llm = openai({ apiKey: OPENAI_API_KEY, model: "gpt-5" });

  const agent = createAgent({
    name: "composio_tool_router_with_llamaindex",
    description:
      "An agent that uses Composio Tool Router MCP tools to perform actions.",
    systemPrompt:
      "You are a helpful assistant connected to Composio Tool Router."+
"Use the available tools to answer user queries and perform Splitwise actions." ,
    llm,
    tools,
  });

  return agent;
}

async function chatLoop(agent: ReturnType<typeof createAgent>) {
  const rl = readline.createInterface({ input, output });

  console.log("Type 'quit' or 'exit' to stop.");

  while (true) {
    let userInput: string;

    try {
      userInput = (await rl.question("\nYou: ")).trim();
    } catch {
      console.log("\nAgent: Bye!");
      break;
    }

    if (!userInput) {
      continue;
    }

    const lower = userInput.toLowerCase();
    if (lower === "quit" || lower === "exit") {
      console.log("Agent: Bye!");
      break;
    }

    try {
      process.stdout.write("Agent: ");

      const stream = agent.runStream(userInput);
      let finalResult: any = null;

      for await (const event of stream) {
        // The event.data contains the streamed content
        const data: any = event.data;

        // Check for streaming delta content
        if (data?.delta) {
          process.stdout.write(data.delta);
        }

        // Store final result for fallback
        if (data?.result || data?.message) {
          finalResult = data;
        }
      }

      // If no streaming happened, show the final result
      if (finalResult) {
        const answer =
          finalResult.result ??
          finalResult.message?.content ??
          finalResult.message ??
          "";
        if (answer && typeof answer === "string" && !answer.includes("[object")) {
          process.stdout.write(answer);
        }
      }

      console.log(); // New line after streaming completes
    } catch (err: any) {
      console.error("\nAgent error:", err?.message ?? err);
    }
  }

  rl.close();
}

async function main() {
  try {
    const agent = await buildAgent();
    await chatLoop(agent);
  } catch (err: any) {
    console.error("Failed to start agent:", err?.message ?? err);
    process.exit(1);
  }
}

main();
```

## Conclusion

You've successfully connected Splitwise to LlamaIndex through Composio's Tool Router MCP layer.
Key takeaways:
- Tool Router dynamically exposes Splitwise tools through an MCP endpoint
- LlamaIndex's ReActAgent handles reasoning and orchestration; Composio handles integrations
- The agent becomes more capable without increasing prompt size
- Async Python provides clean, efficient execution of agent workflows
You can easily extend this to other toolkits like Gmail, Notion, Stripe, GitHub, and more by adding them to the toolkits parameter.

## How to build Splitwise MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/splitwise/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/splitwise/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/splitwise/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/splitwise/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/splitwise/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/splitwise/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/splitwise/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/splitwise/framework/cli)
- [Google ADK](https://composio.dev/toolkits/splitwise/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/splitwise/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/splitwise/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/splitwise/framework/mastra-ai)
- [CrewAI](https://composio.dev/toolkits/splitwise/framework/crew-ai)

## Related Toolkits

- [Stripe](https://composio.dev/toolkits/stripe) - Stripe is a global online payments platform offering APIs for managing payments, customers, and subscriptions. Trusted by businesses for secure, efficient, and scalable payment processing worldwide.
- [Alpha vantage](https://composio.dev/toolkits/alpha_vantage) - Alpha Vantage is a financial data platform offering real-time and historical stock market APIs. Get instant, reliable access to equities, forex, and technical analysis data for smarter trading decisions.
- [Altoviz](https://composio.dev/toolkits/altoviz) - Altoviz is a cloud-based billing and invoicing platform for businesses. It streamlines online payments, expense tracking, and customizable invoice management.
- [Benzinga](https://composio.dev/toolkits/benzinga) - Benzinga provides real-time financial news and data APIs for market coverage. It helps you track breaking news and actionable market insights instantly.
- [Brex](https://composio.dev/toolkits/brex) - Brex provides corporate credit cards and spend management tailored for startups and tech businesses. It helps optimize company cash flow, streamline accounting, and accelerate business growth.
- [Chaser](https://composio.dev/toolkits/chaser) - Chaser is accounts receivable automation software that sends invoice reminders and helps businesses get paid faster. It streamlines the collections process to save time and improve cash flow.
- [Clientary](https://composio.dev/toolkits/clientary) - Clientary is a platform for managing clients, invoices, projects, proposals, and more. It streamlines client work and saves you serious admin time.
- [Coinbase](https://composio.dev/toolkits/coinbase) - Coinbase is a platform for buying, selling, and storing cryptocurrency. It makes exchanging and managing crypto simple and secure for everyone.
- [Coinranking](https://composio.dev/toolkits/coinranking) - Coinranking is a comprehensive cryptocurrency market data platform offering access to real-time coin prices, market caps, and historical data. Get accurate, up-to-date stats for thousands of digital assets in one place.
- [Coupa](https://composio.dev/toolkits/coupa) - Coupa is a business spend management platform for procurement, invoicing, and expenses. It helps organizations streamline purchasing, control costs, and gain complete visibility over financial operations.
- [CurrencyScoop](https://composio.dev/toolkits/currencyscoop) - CurrencyScoop is a developer-friendly API for real-time and historical currency exchange rates. Easily access fiat and crypto data for smart, up-to-date financial applications.
- [Daffy](https://composio.dev/toolkits/daffy) - Daffy is a modern charitable giving platform with a donor-advised fund. Easily set aside funds, grow them tax-free, and donate to over 1.7 million U.S. charities.
- [Eagle doc](https://composio.dev/toolkits/eagle_doc) - Eagle doc is an AI-powered OCR API for invoices and receipts. It delivers fast, reliable, and accurate document data extraction for seamless automation.
- [Elorus](https://composio.dev/toolkits/elorus) - Elorus is an online invoicing and time-tracking software for freelancers and small businesses. Easily manage finances, bill clients, and track work in one place.
- [Eodhd apis](https://composio.dev/toolkits/eodhd_apis) - Eodhd apis delivers comprehensive financial data, including live and historical stock prices, via robust APIs. Easily access reliable, up-to-date market insights to power your apps, dashboards, and analytics.
- [Fidel api](https://composio.dev/toolkits/fidel_api) - Fidel api is a secure platform for linking payment cards to web and mobile apps. It enables real-time card transaction monitoring and event-based automation for businesses.
- [Finage](https://composio.dev/toolkits/finage) - Finage is a secure API platform delivering real-time and historical financial data for stocks, forex, crypto, indices, and commodities. It empowers developers and businesses to access, analyze, and act on market data instantly.
- [Finmei](https://composio.dev/toolkits/finmei) - Finmei is an invoicing tool that simplifies billing, invoice management, and expense tracking. Ideal for automating and organizing your business finances in one place.
- [Fixer](https://composio.dev/toolkits/fixer) - Fixer is a currency data API offering real-time and historical exchange rates for 170 currencies. Instantly access accurate, up-to-date forex data for your applications and workflows.
- [Fixer io](https://composio.dev/toolkits/fixer_io) - Fixer.io is a lightweight API for real-time and historical foreign exchange rates. It makes global currency conversion fast, accurate, and hassle-free.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Splitwise MCP?

With a standalone Splitwise MCP server, the agents and LLMs can only access a fixed set of Splitwise tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Splitwise and many other apps based on the task at hand, all through a single MCP endpoint.

### Can I use Tool Router MCP with LlamaIndex?

Yes, you can. LlamaIndex 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 Splitwise tools.

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

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

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