Lunchmoney MCP Server: Connecting AI Applications to Financial Data

Overview: What is Lunchmoney MCP Server?

Lunchmoney MCP Server is an innovative Model Context Protocol (MCP) server that enables integration between AI applications and financial data from Lunchmoney. This server acts as a bridge, allowing services like Claude Desktop, Continue, Cursor, and more to access and analyze your personal finance transactions and budget details seamlessly.

🔧 Core Features & MCP Capabilities

Lunchmoney MCP Server supports four key functionalities that enhance AI application capabilities:

1. get-recent-transactions: Retrieve recent financial transactions from the past N days.
2. search-transactions: Search through transactions by keyword in payee names or notes.
3. get-category-spending: Analyze spending patterns within specific categories.
4. get-budget-summary: Provide detailed budget information, including actual spendings, remaining amounts, and recurring items.

Each feature leverages MCP to ensure secure, user-approved interactions between AI applications and your personal finance data. This integration fosters a robust ecosystem of AI tools that can offer valuable insights into financial management.

⚙️ MCP Architecture & Protocol Implementation

MCP Client Compatibility Matrix

The Lunchmoney MCP Server supports compatibility with several popular MCP clients:

MCP Client	Resources	Tools	Prompts	Status
Claude Desktop	✅	✅	✅	Full Support
Continue	✅	✅	✅	Full Support
Cursor	❌	✅	❌	Tools Only

MCP Protocol Flow Diagram

The following diagram illustrates the interaction flow between AI applications, Lunchmoney MCP Server, and Lunchmoney:

graph TD
    A[AI Application] -->|MCP Client| B[MCP Protocol]
    B --> C[MCP Server]
    C --> D[Data Source/Tool]
    style A fill:#e1f5fe
    style C fill:#f3e5f5
    style D fill:#e8f5e8

🚀 Getting Started with Installation

Installing via Smithery

To automatically install Lunchmoney MCP Server for Claude Desktop using Smithery:

npx -y @smithery/cli install @leafeye/lunchmoney-mcp-server --client claude

Alternatively, you can use the server directly in your AI workflow:

{
  "mcpServers": {
    "lunchmoney": {
      "command": "npx",
      "args": ["-y", "lunchmoney-mcp-server"],
      "env": {
        "LUNCHMONEY_TOKEN": "your_token_here"
      }
    }
  }
}

Replace your_token_here with your Lunchmoney API token.

💡 Key Use Cases in AI Workflows

Transactions

• "Show me my recent transactions from the past week"
• "Search for all transactions at Amazon"
• "How much did I spend on restaurants last month?"
• "Find transactions tagged as business expenses"

These queries can be easily performed with Lunchmoney MCP Server, providing users with granular control over their financial data.

Budgets

• "Show me my budget summary for this month"
• "What's my budget status from January to March 2024?"
• "How much of my food budget is remaining?"
• "Show me categories where I'm over budget"

These use cases demonstrate how AI applications can leverage Lunchmoney MCP Server to offer advanced financial analysis and budget management.

🔌 Integration with MCP Clients

Lunchmoney MCP Server seamlessly integrates with popular AI clients, enabling a wide range of functionality. For instance, users can execute the following commands within Claude Desktop:

{
  "mcpServers": {
    "lunch money": {
      "command": "npx",
      "args": ["-y", "lunchmoney-mcp-server"],
      "env": {
        "LUNCHMONEY_TOKEN": "your_token_here"
      }
    }
  }
}

This setup allows seamless interaction with AI applications, leveraging Lunchmoney's financial data.

📊 Performance & Compatibility Matrix

Compatibility and performance are critical aspects of any MCP server. Here’s a brief overview:

• Transaction Retrieval: Efficient retrieval of recent transactions.
• Search Functionality: Rapid search through vast transaction datasets.
• Budget Analysis: Accurate calculation of budget spending.

The Lunchmoney MCP Server has been designed to ensure optimal performance across various AI applications, ensuring reliable and fast data access.

🛠️ Advanced Configuration & Security

Configuration Code Sample

{
  "mcpServers": {
    "lunchmoney": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-lunchmoney"],
      "env": {
        "LUNCHMONEY_TOKEN": "your_api_key_here"
      }
    }
  }
}

Security Measures

To ensure data privacy and security, all interactions through Lunchmoney MCP Server require user approval. This is implemented via the MCP protocol, ensuring secure and transparent transactions.

❓ Frequently Asked Questions (FAQ)

1. How does Lunchmoney MCP Server enhance AI applications?

   • By providing a standardized way to connect AI models with financial data, offering deeper insights and analytics.

2. Can I use this server with other AI clients besides Claude Desktop?

   • Yes, the Lunchmoney MCP Server supports multiple MCP clients such as Continue and Cursor.

3. What types of financial data can be accessed via this server?

   • You can access transaction history, budget information, categories, and more.

4. Is there a limit to the number of transactions I can search at once?

   • No, but performance may vary based on the size of the dataset.

5. How do I handle API token security?

   • Ensure your API keys are stored securely and not exposed in public repositories or shared files.

👨‍💻 Development & Contribution Guidelines

Contributions to the Lunchmoney MCP Server are welcomed! Please submit Pull Requests with detailed descriptions of your changes.

Installation Steps

1. Clone this repository.
2. Install dependencies:

   npm install
   

3. Build the TypeScript code:

   npm run build
   

4. Run the server with an API token:

   LUNCHMONEY_TOKEN=your_token_here node build/index.js
   

5. Test with MCP Inspector:

   LUNCHMONEY_TOKEN=your_token_here npx @modelcontextprotocol/inspector node build/index.js
   

🌐 MCP Ecosystem & Resources

For more information on MCP and its applications, visit Model Context Protocol.

The Lunchmoney MCP Server is built to be a cornerstone in the growing ecosystem of AI application integrations. By connecting AI clients with your financial data, it offers unparalleled opportunities for personal finance management and analysis.

This comprehensive documentation positions the Lunchmoney MCP Server as a key component in enhancing the capabilities of AI applications through secure and standardized data access.