society-maintenance-mcp-server

society-maintenance-mcp-server

Enables querying society maintenance and expense data from Excel files via natural language, providing tools to check pending payments, balance sheets, expense summaries, and flat histories.

Category
Visit Server

README

Society Maintenance Tracker — MCP Server

An MCP (Model Context Protocol) server that exposes society maintenance and expense data as tools, so any MCP-compatible AI agent (Claude Desktop, Cursor, watsonx, etc.) can query it using natural language.


What it does

The server reads two Excel files (Maintenance.xlsx and Expenses.xlsx) and registers 8 tools that an AI agent can call:

Tool What it answers
tool_get_all_months Which months have data?
tool_get_pending_maintenance Which flats haven't paid? (by month or year)
tool_get_collected_maintenance Which flats have paid? (by month or year)
tool_get_balance_sheet Income vs expenses — surplus or deficit?
tool_get_expense_summary Expenses broken down by category
tool_get_flat_history Full payment history for a specific flat
tool_download_pending_report Generate & save pending maintenance Excel report
tool_download_balance_report Generate & save balance sheet Excel report

Project structure

Society Maintenance Tracker/
├── server.py               # MCP server entry point (8 tools registered)
├── server/
│   ├── __init__.py
│   └── data_loader.py      # Loads & queries Maintenance.xlsx + Expenses.xlsx
├── reports/
│   ├── __init__.py
│   └── generator.py        # Generates styled Excel reports
├── data/                   # ← YOU must supply these (not included in repo)
│   ├── Maintenance.xlsx
│   └── Expenses.xlsx
├── downloads/              # Auto-created — generated reports saved here
├── requirements.txt
├── Dockerfile
└── README.md

Prerequisites

  • Python 3.11 or 3.12
  • The two Excel data files (see Data files below)

Installation

1. Clone the repo

git clone https://github.com/YOUR_USERNAME/society-maintenance-tracker.git
cd society-maintenance-tracker

2. Create a virtual environment (recommended)

python -m venv .venv

# Windows
.venv\Scripts\activate

# macOS / Linux
source .venv/bin/activate

3. Install dependencies

pip install -r requirements.txt

4. Add your data files

Create a data/ folder and place your Excel files inside:

data/
├── Maintenance.xlsx    ← sheet name must be "Maintenance"
└── Expenses.xlsx       ← sheet name must be "Expenses"

Expected columns:

Maintenance.xlsx — Month | Date | Flat No | Name | Amount | Late Charges

Expenses.xlsx — Month | Date | Expence Type | Details | Amount | Spend By


Running the server

stdio mode — for AI agents that spawn it as a subprocess (Claude Desktop, Cursor, etc.)

python server.py

⚠️ Do not type into the terminal in this mode — the server speaks JSON-RPC over stdin/stdout. It will look frozen; that is normal.

SSE mode — for persistent servers / external clients

python server.py --sse

Server listens at http://localhost:8100/sse.


Connecting to AI clients

Claude Desktop

Edit %APPDATA%\Claude\claude_desktop_config.json (Windows) or ~/Library/Application Support/Claude/claude_desktop_config.json (macOS):

{
  "mcpServers": {
    "society-maintenance": {
      "command": "python",
      "args": ["C:/full/path/to/society-maintenance-tracker/server.py"]
    }
  }
}

Restart Claude Desktop. You can now ask questions like:

  • "Which flats haven't paid maintenance for January 2024?"
  • "What is the balance sheet for 2024?"
  • "Give me the payment history for flat 601."

Cursor / VS Code (MCP extension)

Add to your MCP settings:

{
  "society-maintenance": {
    "command": "python",
    "args": ["/full/path/to/server.py"]
  }
}

MCP Inspector (browser UI — best for testing)

npx @modelcontextprotocol/inspector python server.py

Opens at http://localhost:5173 — browse and call all tools interactively.


Running with Docker

# Build
docker build -t society-mcp .

# Run (mount your local data/ folder into the container)
docker run -v $(pwd)/data:/app/data society-mcp

Testing

Quick data sanity check

python -c "
import sys; sys.path.insert(0, '.')
from server.data_loader import get_all_months, get_balance_sheet
print(get_all_months())
print(get_balance_sheet(year=2024))
"

Full MCP protocol test (stdio)

python _test_server.py

This sends a proper JSON-RPC handshake and lists all registered tools.


Data files

The data/ folder is excluded from this repository (see .gitignore) because the Excel files contain private resident information.

To use this server:

  1. Create your own Maintenance.xlsx and Expenses.xlsx following the column format above.
  2. Place them in the data/ folder.
  3. The server will load them automatically on first tool call.

Month format

Months in the Excel file must follow the pattern MonthName_YYYY, e.g.:

Jan_2024   Feb_2024   March_2024   April_2024
May_2024   June_2024  July_2024    Aug_2024
Sep_2024   Oct_2024   Nov_2024     Dec_2024

The server normalises common variants automatically (january_2024, MARCH_2025, jun_2024, etc.).


License

MIT

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured