Financial Calculators MCP Server
Provides educational fixed-rate loan estimates with mortgage and auto loan calculators.
README
Financial Calculators ChatGPT App
A greenfield ChatGPT app/plugin starter with a TypeScript MCP server and a vanilla financial calculators widget.
The app exposes read-only tools for educational fixed-rate loan estimates. It does not use an OpenAI API key or any external financial API.
What It Includes
- MCP server at
http://localhost:8787/mcp - Health endpoint at
http://localhost:8787/health calculate_mortgagetool with structured outputcalculate_auto_loantool with structured output- Inline widget at
ui://widget/mortgage-calculator.html - Mortgage sliders for home price, down payment, interest rate, term, taxes, insurance, HOA, PMI, and extra payments
- Auto loan sliders for vehicle price, down payment, trade-in, interest rate, term, sales tax, fees, and extra payments
- Focused unit tests for mortgage math
Local Development
npm install
npm run dev
In another terminal:
npm run inspector
The inspector command uses MCP Inspector against:
http://localhost:8787/mcp
Test In ChatGPT Developer Mode
- Start the local server with
npm run dev. - Expose it over HTTPS with Secure MCP Tunnel, ngrok, or Cloudflare Tunnel.
- In ChatGPT, enable Developer Mode.
- Create a developer-mode app/plugin and use the public MCP URL, ending in
/mcp. - Refresh the app metadata after changing tool names, descriptions, schemas, or widget metadata.
Example Prompt
Use the mortgage calculator to estimate the monthly payment for a $400,000 home with $80,000 down, a 6.5% fixed rate, a 30-year term, $6,000 annual property tax, and $1,800 annual homeowners insurance.
Use the auto loan calculator to estimate the monthly payment for a $42,000 vehicle with $5,000 down, a $3,000 trade-in, 7.25% APR, a 60-month term, 6.25% sales tax, and $900 in fees.
Safety Note
This app is for educational estimates only. It is not financial, lending, tax, or legal advice. Production versions should add stronger disclosures, localization, logging, monitoring, and review-specific metadata before public submission.
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