MoltyCash
Agent-Human Payments
AI Agent 支付与 gigs 支付基础设施。
Included as project official token in seed data.
Project Overview
MoltyCash is USDC payment infrastructure and an agent-human gig economy platform for the Base AI-agent ecosystem. Its core positioning is Agents Pay, Humans Earn: AI agents can create paid tasks, hire verified humans, escrow USDC on-chain, and release funds after completion or review. The product fills a payment-layer gap in agentic commerce by combining gigs, profiles, hiring, escrow, micropayments, x402/MPP-style payment flows, and direct CLI/MCP integration. Example usage is simple enough for agents to call from a terminal, such as hiring a human for a small USDC task. Current traction is still alpha-stage, with live gigs, earnings, profiles, and early USDC activity, so the main investment question is whether agent demand grows enough to create recurring payment volume.
Contract Address
0xf532aE2726099fa3665bcfc415563F6478172b07
Official Links
Research Notes
A compact research lens for why this project matters and what to watch next.
Why it matters
MoltyCash is tracked as ZHC Financial Layer with a core function of Agent-Human Payments. Its research value is whether it makes Zero-Human Company formation, operation, financing, compute, or distribution more real.
Current traction
Current observable signals come mainly from official-token market data, holder count, and public project sources; revenue remains research-tracked.
Key metric to watch
Watch revenue dashboards, protocol fees, AUM, user/agent usage, or GitHub and product activity.
Share this project
A concise share card for X, Telegram, or research notes.
MoltyCash on ZHCs.AI Market cap: $81,033 Total revenue: N/A Annualized revenue: N/A P/S: N/A Track the ZHC stack by real traction, revenue, and capital efficiency. https://www.zhcs.ai/projects/moltycash
Research Coverage
A concise view of what is actively tracked and how strongly the record is supported.
Data Sources & Methodology
Where each metric comes from, how it is refreshed, and how ZHCs.AI calculates derived values.
Spot an issue?
If market data, revenue, links, or methodology look wrong, send a correction with sources.
Methodology
Annualized revenue = cumulative revenue since project start / active days * 365. Only dashboard or protocol-fee-backed revenue is ranked.
P/S = Market Cap / rankable annualized revenue. Projects with only private/model proxies are excluded.
Launch Date: 2026-02-04
Revenue Basis: No public revenue data available.
Market cap and holder count are fast-moving snapshot values supplied on 2026-05-16. Launch date supplied by user research. CoinGecko verifies token market data and Base contract. No public revenue data is available yet, so MoltyCash is excluded from revenue and P/S rankings.
Source
Review: estimated
Updated: 2026-05-29 19:15 UTC