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Splitwise MCP Server for LangChainGive LangChain instant access to 10 tools to Create Expense, Delete Expense, Get Current User, and more

Built by Vinkius GDPR 10 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Splitwise through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Ask AI about this App Connector for LangChain

The Splitwise app connector for LangChain 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

python
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "splitwise": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Splitwise, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())
Splitwise
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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.

LangChain's ecosystem of 500+ components combines seamlessly with Splitwise through native MCP adapters. Connect 10 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

The Splitwise MCP Server exposes 10 tools through the Vinkius. Connect it to LangChain 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 LangChain

When LangChain 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.

create_expense

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_expense

Delete an expense

get_current_user

Get current user details

get_expense

Get a specific expense

get_expenses

List expenses

get_friend

Get friend details

get_friends

List all friends

get_group

Get group details

get_groups

List all groups

get_user

Get user details by ID

Connect Splitwise to LangChain via MCP

Follow these steps to wire Splitwise into LangChain. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

01

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save the code and run python agent.py
04

Explore tools

The agent discovers 10 tools from Splitwise via MCP

Why Use LangChain with the Splitwise MCP Server

LangChain provides unique advantages when paired with Splitwise through the Model Context Protocol.

01

The largest ecosystem of integrations, chains, and agents. combine Splitwise MCP tools with 500+ LangChain components

02

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

03

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

04

Memory and conversation persistence let agents maintain context across Splitwise queries for multi-turn workflows

Splitwise + LangChain Use Cases

Practical scenarios where LangChain combined with the Splitwise MCP Server delivers measurable value.

01

RAG with live data: combine Splitwise tool results with vector store retrievals for answers grounded in both real-time and historical data

02

Autonomous research agents: LangChain agents query Splitwise, synthesize findings, and generate comprehensive research reports

03

Multi-tool orchestration: chain Splitwise tools with web scrapers, databases, and calculators in a single agent run

04

Production monitoring: use LangSmith to trace every Splitwise tool call, measure latency, and optimize your agent's performance

Example Prompts for Splitwise in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with Splitwise immediately.

01

"Check how much I currently owe in the 'Paris Trip' group."

02

"Add a new $100 expense for Uber rides to Splitwise and split it equally with Jane."

03

"List all my friends connected on Splitwise."

Troubleshooting Splitwise MCP Server with LangChain

Common issues when connecting Splitwise to LangChain through the Vinkius, and how to resolve them.

01

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Splitwise + LangChain FAQ

Common questions about integrating Splitwise MCP Server with LangChain.

01

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.
02

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.
03

Can I trace MCP tool calls in LangSmith?

Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.