Splitwise MCP Server for Pydantic AIGive Pydantic AI instant access to 10 tools to Create Expense, Delete Expense, Get Current User, and more
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Splitwise through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
Ask AI about this App Connector for Pydantic AI
The Splitwise app connector for Pydantic AI 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 pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
agent = Agent(
model="openai:gpt-4o",
mcp_servers=[server],
system_prompt=(
"You are an assistant with access to Splitwise "
"(10 tools)."
),
)
result = await agent.run(
"What tools are available in Splitwise?"
)
print(result.data)
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.
Pydantic AI validates every Splitwise tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.
The Splitwise MCP Server exposes 10 tools through the Vinkius. Connect it to Pydantic AI 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 Pydantic AI
When Pydantic AI 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 Pydantic AI via MCP
Follow these steps to wire Splitwise into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install Pydantic AI
pip install pydantic-aiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use Pydantic AI with the Splitwise MCP Server
Pydantic AI provides unique advantages when paired with Splitwise through the Model Context Protocol.
Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Splitwise integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Splitwise connection logic from agent behavior for testable, maintainable code
Splitwise + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Splitwise MCP Server delivers measurable value.
Type-safe data pipelines: query Splitwise with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Splitwise tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Splitwise and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Splitwise responses and write comprehensive agent tests
Example Prompts for Splitwise in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI 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 Pydantic AI
Common issues when connecting Splitwise to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiSplitwise + Pydantic AI FAQ
Common questions about integrating Splitwise MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.