Finance MCP Server

A Model Context Protocol server exposing personal-finance tools — accounts, transactions, spending analysis, budgets, bills, reminders, portfolio, and goals — so any MCP client (Claude Desktop, Claude Code, custom agents) can query financial data through a standard interface.

The tool layer is shared with finance-copilot: same deterministic sample dataset, same eight tools, different transport — there they're wired into a bespoke agentic loop; here they're served over MCP.

Tools

Tool	Purpose
get_accounts	Balances across checking/savings/credit/brokerage/401(k) + net worth
get_transactions	Individual transactions, filterable by month and category
analyze_spending	Per-category monthly totals, trends, top merchants
get_budgets	Budget vs. actual for the current month with over/under status
get_bills	Recurring bills with next due dates and due-soon flags
set_bill_reminder	Create a reminder N days before a bill is due
get_portfolio	Holdings, gains/losses, asset allocation
get_financial_goals	Savings goals with progress + income/risk profile

Setup

python3 -m venv .venv && .venv/bin/pip install -r requirements.txt
.venv/bin/python test_client.py   # smoke test: lists tools, calls three

If pip tries to compile cryptography from source (Anaconda x86_64 Python without a matching wheel), create the venv with python3 -m venv .venv --system-site-packages to reuse the system copy.

Connect a client

Claude Code:

claude mcp add finance -- /path/to/finance-mcp-server/.venv/bin/python /path/to/finance-mcp-server/server.py

Claude Desktop (claude_desktop_config.json):

{
  "mcpServers": {
    "finance": {
      "command": "/path/to/finance-mcp-server/.venv/bin/python",
      "args": ["/path/to/finance-mcp-server/server.py"]
    }
  }
}

Then ask: "How am I tracking against my budget this month?" — the client discovers the tools automatically and the model calls them as needed.

Design notes

• FastMCP generates tool schemas from Python type hints and docstrings — the schemas stay in sync with the code by construction.
• stdio transport — the client spawns the server as a subprocess; no ports, no network exposure.
• Demo data — finance_data.py generates a deterministic fake bank (fixed seed). Swap it for a real aggregator (e.g. Plaid) to serve live data; the MCP surface doesn't change.
• test_client.py doubles as a minimal example of driving an MCP server programmatically with the Python SDK.