Finance Intelligence Mcp

io.github.Ronit-019Published by GitHub account Ronit-019v1.0.0Updated Oct 24, 2026

Personal finance MCP server with budgeting, analytics, and PostgreSQL.

The publisher's own server: Finance Foundation

VerifiedSTDIODesktop onlyDatabasesFinanceData & Analytics

Overview

AI-generated overview

A local MCP server that lets an AI assistant record, edit and analyze personal expenses and budgets stored in your own PostgreSQL database.

What you can do
Add, list, update and bulk-delete expense entries, with large lists exported to Excel spreadsheets. Create, list, update and delete overall, category and subcategory budgets. Aggregate spending by category, subcategory, note or date over weekly, monthly or yearly periods. Compare budgets against actual spending and generate Matplotlib line or bar charts of spending history. Calculate a financial health score from six personal finance indicators.
When to use it
Useful if you keep personal finance data in a PostgreSQL database and want to log expenses, check budget status, get spending breakdowns and charts, or review a financial health score through natural-language prompts in a desktop MCP client.
Requirements
Runs locally over stdio as a PyPI package (finance-intelligence-mcp) with Python 3.10 to 3.12, installed via uv or pip. Needs a PostgreSQL 12+ database, such as Supabase, RDS or a local instance, supplied through the required DATABASE_URL environment variable. Desktop MCP clients such as Claude Desktop or Cursor are the documented targets.
Before you install
DATABASE_URL is a secret connection string that includes your database password; keep it out of shared configs and logs. The server can write to and permanently delete expense and budget records, and bulk-delete tools act on filters, so confirm targets before running them. All financial data stays in your own database; the README states there is no telemetry or external analytics.

Installation

In SourceWeft

  1. Open Finance Intelligence Mcp in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

Finance Intelligence MCP Server

[Python Version] [FastMCP] [License: MIT] [MCP Specification] [Database]

Finance Intelligence MCP is a production-ready Model Context Protocol (MCP) server that enables AI assistants (like Claude, Cursor, and others) to securely manage and analyze personal finances through natural language.

Released under the MIT License and designed to be extended with additional finance tools.

🔍 Overview

Unlike standard cloud-based personal finance apps, Finance Intelligence MCP keeps all financial data under your absolute control.

  • No Accounts / Subscriptions: Direct connection to your private database with zero SaaS dependencies.
  • Zero Telemetry: Your financial logs never go to external analytic APIs.
  • Full AI Context: Your AI assistant can query history, check budget status, make charts, and answer financial questions instantly.

🛠️ Architecture

   ┌────────────────────────────────┐   │           MCP Client           │   │  (Claude Desktop, Cursor, etc) │   └───────────────┬────────────────┘                   │                   │ (STDIO Transport Protocol)                   ▼   ┌────────────────────────────────┐   │  Finance Intelligence Server   │   │           (Local)              │   └───────────────┬────────────────┘                   │                   │ (Direct SQL Pool Connection)                   ▼   ┌────────────────────────────────┐   │       PostgreSQL Database      │   │ (Supabase, Local, RDS, etc)    │   └────────────────────────────────┘

✨ Features

  • Expense Operations: Create, view, edit, and bulk-delete expense entries.
  • Multi-level Budgeting: Set limits for overall spending, specific category thresholds, or down to nested subcategory targets.
  • Analytics Breakdowns: Aggregate expenses by category, subcategory, notes, or dates over weekly/monthly/yearly time blocks.
  • Visual Charts: Exposes tools that generate Matplotlib line/bar charts of historical spending automatically.
  • Excel Spreadsheet Export: Truncates long list responses and generates download-ready Excel spreadsheets for massive datasets.
  • Financial Health Scoring: Calculates a deterministic financial health score grade based on 6 core personal finance KPIs.

⚙️ Requirements & Compatibility

  • Transport: stdio
  • Supported Platforms:
    • Windows
    • macOS
    • Linux
  • Python Compatibility: Python 3.10, 3.11, and 3.12 (Tested)
  • Database: PostgreSQL 12+ (e.g. Supabase, RDS, or local Postgres)
  • Supported Clients:
    • Claude Desktop
    • Cursor
    • Compatible with any MCP client supporting stdio.

💾 Installation & Setup

1. Quick Setup (Shortcut)

If you have uv installed, get started in 2 lines:

bash
git clone https://github.com/Ronit-019/Finance-Intelligence-MCP.gitcd Finance-Intelligence-MCPuv sync

2. Detailed Installation

Step A: Get a PostgreSQL Connection URL

The easiest, free option is Supabase:

  1. Go to Supabase and create a free project.
  2. Go to Project Settings (gear icon) > Database.
  3. Under Connection string, select URI and copy the string.
    • Example: postgresql://postgres.[your-project-ref]:[your-password]@aws-0-us-east-1.pooler.supabase.com:5432/postgres
    • (Replace [your-password] with your database password).
Step B: Clone the Repository

Clone the codebase to a directory on your machine:

bash
git clone https://github.com/Ronit-019/Finance-Intelligence-MCP.gitcd Finance-Intelligence-MCP

Copy the absolute path of this directory (e.g. C:/Users/Admin/Desktop/Finance-Intelligence-MCP). Note: Always use forward slashes (/) for paths in JSON configs.

Step C: Install Dependencies

If you do not have uv installed, install from the project metadata:

bash
pip install -e .

3. Client Integration

Claude Desktop Setup
  1. Open your Claude configuration file (claude_desktop_config.json):
    • Windows: Press Win + R, paste %APPDATA%\Claude\claude_desktop_config.json and press Enter.
    • macOS: Paste ~/Library/Application Support/Claude/claude_desktop_config.json in Finder's Go to Folder.
  2. Add this entry to mcpServers:
json
{  "mcpServers": {    "finance-intelligence": {      "command": "uv",      "args": [        "--directory",        "REPLACE_WITH_ABSOLUTE_PATH_TO_CLONED_DIRECTORY",        "run",        "python",        "main.py"      ],      "env": {        "DATABASE_URL": "REPLACE_WITH_YOUR_SUPABASE_CONNECTION_STRING"      }    }  }}
  1. Save and completely restart Claude Desktop.
Cursor IDE Setup
  1. Go to Settings > Features > MCP.
  2. Click + Add New MCP Server:
    • Name: Finance Intelligence
    • Type: command
    • Command:
      bash
      uv --directory "REPLACE_WITH_ABSOLUTE_PATH_TO_CLONED_DIRECTORY" run python main.py
  3. Click + Add Env Var:
    • Key: DATABASE_URL
    • Value: REPLACE_WITH_YOUR_SUPABASE_CONNECTION_STRING
  4. Click Save and refresh.

💬 Example Prompts

Once configured, try talking to your AI assistant:

  • "Add ₹250 for lunch today under food."
  • "Show my spending breakdown this month."
  • "Generate an Excel report of all my expenses between May and July."
  • "Am I exceeding my monthly budget limit?"
  • "How much did I spend on dining out this week?"
  • "Calculate my monthly financial health score and give me feedback."
  • "Generate a spending chart for the last 30 days."

🛠️ Available Tools

The server registers 12 core tools on the client:

Tool NameParametersDescription
add_expensedate, amount, category, subcategory, noteInserts a new expense transaction.
list_expensesstart_date, end_dateLists transactions, exports to Excel if count > 50.
expense_breakdownstart_date, end_date, group_by, breakdown, category, subcategoryAggregates spending sums and counts.
delete_expensesexpense_ids, start_date, end_date, category, subcategoryDeletes expenses matching filters.
update_expensesexpense_ids, filter_..., date, amount, category, subcategory, noteEdits expense records.
create_budgetbudget_type, amount, period, start_date, end_date, category, subcategory, budgetsRegisters new spending limits.
list_budgetsbudget_type, category, subcategory, periodReturns registered budgets.
update_budgetsbudget_ids, filter_..., budget_type, amount, period, start_date, end_date, category, subcategoryModifies active budgets.
delete_budgetsbudget_ids, start_date, end_date, budget_type, category, subcategory, periodDeletes target budget limits.
compare_budget_vs_expensesreference_date, budget_type, category, subcategory, periodCompares budget vs actual spending.
expense_summaryperiod, group_by, category, subcategory, start_date, end_dateGenerates a Matplotlib line/bar chart.
financial_health_scorereference_monthEvaluates 6 key personal finance indicators.

💡 Troubleshooting

1. uv: command not found

If the client cannot locate uv, update your config file to run standard Python:

  • Ensure you ran pip install -e . inside the repository.
  • Update config:
json
"finance-intelligence": {  "command": "python",  "args": [    "REPLACE_WITH_ABSOLUTE_PATH_TO_CLONED_DIRECTORY/main.py"  ],  "env": {    "DATABASE_URL": "REPLACE_WITH_YOUR_SUPABASE_CONNECTION_STRING"  }}

2. Invalid DATABASE_URL / PostgreSQL Connection Errors

  • Make sure you replaced [your-password] with your actual database password in the Supabase URI string.
  • Ensure there are no surrounding spaces or special characters in the URL string.
  • Verify your Supabase instance is active and not paused.

3. Claude Not Detecting the Server

  • Double check that the folder paths in claude_desktop_config.json use forward slashes (/), even on Windows.
  • Check the logs at %APPDATA%\Claude\logs\mcp*.log (Windows) or ~/Library/Logs/Claude/mcp*.log (macOS) to see the exact startup error.

📁 Repository Structure

├── src/                       # Helper packages│   ├── __init__.py│   ├── budget.py              # Budget database operations│   ├── analytics.py           # Breakdown aggregations & Matplotlib routines│   └── health.py              # KPIs and financial health calculator├── main.py                    # FastMCP Server application├── categories.json            # Category mapping catalog├── pyproject.toml             # Dependencies├── LICENSE                    # MIT License file└── README.md                  # This file

🤝 Contributing

Contributions, bug reports, and feature requests are welcome! Please open an issue before submitting major changes or pull requests.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

👨‍💻 Author

Ronit Rajput

Source: README.md at commit af79c0c

Tools

0
SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

1
  1. v1.0.0LatestSep 16, 2026

Score

50% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 days25 pts

    Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.

  • Auth declared10 pts

    Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.

  • Tools listed15 pts

    Answer tools/list without a credential, or ship a package that starts in a sandbox without one.

  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts

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