Splitwise MCP Server for LlamaIndexGive LlamaIndex instant access to 10 tools to Create Expense, Delete Expense, Get Current User, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Splitwise as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
Ask AI about this App Connector for LlamaIndex
The Splitwise app connector for LlamaIndex is a standout in the Productivity category — giving your AI agent 10 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Splitwise. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Splitwise?"
)
print(response)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Splitwise MCP Server
What you can do
- Track Expenses: Give your AI agent the ability to check who owes who across your distinct groups.
- Log Bills: Ask your AI to calculate receipts and accurately add the expense directly into Splitwise with automatic percentage or custom splits.
- Manage Friends & Groups: Easily pull details of group members.
LlamaIndex agents combine Splitwise tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
The Splitwise MCP Server exposes 10 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 10 Splitwise tools available for LlamaIndex
When LlamaIndex connects to Splitwise through Vinkius, your AI agent gets direct access to every tool listed below — spanning expense-tracking, bill-splitting, debt-management, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Expects a stringified JSON object containing details like cost, description, format details (e.g. users__0__user_id=123, users__0__paid_share=5.00, etc. or JSON). Create an expense
Delete an expense
Get current user details
Get a specific expense
List expenses
Get friend details
List all friends
Get group details
List all groups
Get user details by ID
Connect Splitwise to LlamaIndex via MCP
Follow these steps to wire Splitwise into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the Splitwise MCP Server
LlamaIndex provides unique advantages when paired with Splitwise through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Splitwise tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Splitwise tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Splitwise, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Splitwise tools were called, what data was returned, and how it influenced the final answer
Splitwise + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Splitwise MCP Server delivers measurable value.
Hybrid search: combine Splitwise real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Splitwise to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Splitwise for fresh data
Analytical workflows: chain Splitwise queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Splitwise in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Splitwise immediately.
"Check how much I currently owe in the 'Paris Trip' group."
"Add a new $100 expense for Uber rides to Splitwise and split it equally with Jane."
"List all my friends connected on Splitwise."
Troubleshooting Splitwise MCP Server with LlamaIndex
Common issues when connecting Splitwise to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpSplitwise + LlamaIndex FAQ
Common questions about integrating Splitwise MCP Server with LlamaIndex.