A Model Context Protocol (MCP) server that integrates with Splitwise. Connect your AI assistant (Claude, Cursor, etc.) to manage Splitwise expenses using natural language — with voice support!
flowchart LR
Client[Claude / Cursor] -->|MCP| Server[splitwise-mcp]
Server -->|audio| Deepgram[Deepgram STT]
Deepgram -->|text| Gemini[Gemini 3 Flash]
Gemini -->|action| Splitwise[Splitwise API]
| Tool | Description |
|---|---|
voice_command |
Send audio → Deepgram transcribes → Gemini processes → Splitwise executes |
text_command |
Send text → Gemini processes → Splitwise executes |
add_expense |
Add expenses with support for groups, percentages, exclusions, and specific payers |
delete_expense |
Delete an expense by ID |
list_friends |
List your Splitwise friends |
configure_splitwise |
Configure API credentials |
login_with_token |
Login with OAuth2 token |
Smart Name Matching: If Deepgram transcribes "Humeet" but your friend is "Sumeet", Gemini will ask for clarification instead of guessing.
- Percentages: "Split 40% for me and 60% for Alice"
- Groups: "Add to Apartment group" (Auto-fetches members)
- Exclusions: "Add to Apartment but exclude Bob"
- Payer: "Alice paid $50"
- Deletion: "Delete expense 12345"
pip install splitwise-mcp-
Clone the repository:
git clone https://github.com/hubshashwat/the-splitwise-mcp.git cd the-splitwise-mcp -
Create and activate a virtual environment:
python3 -m venv .venv source .venv/bin/activate -
Install the package:
pip install -e .
You'll need API keys depending on which features you want:
- Splitwise API Keys (https://secure.splitwise.com/apps/new)
- Register a new application
- Get: Consumer Key, Consumer Secret, and API Key
- Required for:
add_expense,list_friends,delete_expense
-
Gemini API Key (https://aistudio.google.com/) - Optional
- Create API key (free tier available)
- Model: Uses Gemini 3.0 Flash - ensure your API key has access to this model
- Required for:
text_command(natural language processing)
-
Deepgram API Key (https://console.deepgram.com/) - Optional
- Sign up and get API key (free tier available)
- Required for:
voice_command(audio transcription)
Summary:
- Text-only users: Need Splitwise + Gemini keys (skip Deepgram)
- Voice users: Need all 5 keys
- Basic API users: Only need 3 Splitwise keys
Set environment variables in your shell or add to your Claude Desktop config (see below).
You can use this server in two ways:
Run the voice/text agent directly in your terminal:
# Install the package
pip install splitwise-mcp
# Download the agent script
curl -O https://raw.githubusercontent.com/hubshashwat/the-splitwise-mcp/main/run_agent.py
# Set environment variables
export SPLITWISE_CONSUMER_KEY="your_key"
export SPLITWISE_CONSUMER_SECRET="your_secret"
export SPLITWISE_API_KEY="your_api_key"
export GEMINI_API_KEY="your_gemini_key"
export DEEPGRAM_API_KEY="your_deepgram_key"
# Run the agent
python run_agent.pyCommands:
vorvoice- Record 10 seconds of audio and process ittortext- Type your commandqorquit- Exit
Example session:
🤖 Splitwise Voice Agent
Enter command (voice/text/quit): t
Enter request: Add expense of $50 with John for dinner
⚠️ Proposed Action:
Function: add_expense
Args: {
"description": "dinner",
"cost": 50.0,
"split_with": ["John"]
}
Proceed? (yes/edit/cancel): yes
✅ Expense added!
This server uses stdio transport and works with all MCP-compatible clients:
Add to your config:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"splitwise": {
"command": "full path of python",
"args": ["-m", "splitwise_mcp.server"],
"env": {
"SPLITWISE_CONSUMER_KEY": "your_consumer_key",
"SPLITWISE_CONSUMER_SECRET": "your_consumer_secret",
"SPLITWISE_API_KEY": "your_api_key",
"GEMINI_API_KEY": "your_gemini_key",
"DEEPGRAM_API_KEY": "your_deepgram_key"
}
}
}
}Note: If
splitwise-mcpconsole command is available, you can use"command": "splitwise-mcp"without args instead.
Then in Claude: "Add an expense of $50 with John for dinner"
Use the same config format with claude-cli --mcp-config.
Add to your MCP settings (.vscode/settings.json or Cursor settings):
{
"mcp.servers": {
"splitwise": {
"command": "full path of python",
"args": ["-m", "splitwise_mcp.server"],
"env": {
"SPLITWISE_CONSUMER_KEY": "your_consumer_key",
"SPLITWISE_CONSUMER_SECRET": "your_consumer_secret",
"SPLITWISE_API_KEY": "your_api_key",
"GEMINI_API_KEY": "your_gemini_key",
"DEEPGRAM_API_KEY": "your_deepgram_key"
}
}
}
}Then you can ask your AI assistant: "Use Splitwise to add an expense..."
This server is compatible with any MCP client supporting stdio transport. Use the same configuration pattern.
Note: If you installed from source instead of pip, use the full path to the executable:
- macOS/Linux:
"/path/to/the-splitwise-mcp/.venv/bin/splitwise-mcp" - Windows:
"C:\\path\\to\\the-splitwise-mcp\\.venv\\Scripts\\splitwise-mcp.exe"
To run the MCP server over HTTP for remote clients:
.venv/bin/uvicorn splitwise_mcp.sse:app --host 0.0.0.0 --port 8000Connect via: http://YOUR_IP:8000/sse
Run tests:
.venv/bin/python tests/test_logic.pyIf the agent says "Recording finished" immediately but captures no audio (Volume: 0.0), your terminal likely lacks microphone permission.
- Go to System Settings > Privacy & Security > Microphone.
- Enable access for your terminal app (Terminal, iTerm, VS Code, etc.).
- Restart your terminal for changes to take effect.
MIT