GG402 · AI retirement planning
Create personalized retirement plans with savings projections, risk analysis, and strategy recommendations.
What it does
Create personalized retirement plans with savings projections, risk analysis, and strategy recommendations.
- Build financial wellness apps with retirement calculators
- Generate risk-adjusted savings strategies for users
- Project retirement outcomes based on variable contribution rates
Ideal buyer
Financial planning AI agents and robo-advisor platforms requiring automated retirement projections.
Run this through your governed agent wallet.
- 01Bootstrap AXON once with
npx @axon402/init. - 02Use the AXON runtime MCP tools to
search_x402_servicesorinspect_x402_offerfor this service. - 03Quote, test-buy, then run the governed paid fetch through AXON.
Send this
Prompt for your agent
A natural-language instruction for your LLM agent — with this endpoint exposed as a tool — to call this resource. Not sent to the endpoint; the endpoint consumes the JSON body below.
Pasting this prompt into a raw ChatGPT or unconfigured agent will notexecute the paid endpoint flow. Run it through an agent with the AXON runtime / MCP tools exposed (see “Use with AXON” above) so the 402 challenge, quote, and governed fetch are handled for you.
“Create a retirement plan for a 35-year-old aiming to retire at 65 with $2M target”
Endpoint request body
The JSON payload your agent sends to the endpoint.
{
"current_age": 35,
"target_amount": 2000000,
"retirement_age": 65,
"monthly_contribution": 1500
}Advanced HTTP details
For integrators who need the raw protocol surface. Most agents should use AXON above instead of calling these directly.
Endpoint URL
curl fallback
curl https://gg402.vercel.app/retirement_planner \ -H "Content-Type: application/json" \ -H "X-PAYMENT: [signed_payment_envelope]" \ -d '{"current_age":35,"target_amount":2000000,"retirement_age":65,"monthly_contribution":1500}'
Payment & settlement details
Raw on-chain settlement parameters. AXON above handles these automatically through quote / test-buy / governed fetch.
Price & network
Trust & risk
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