This topic covers API-to-agent monetization platforms and autonomous revenue tools—systems that link developer and no-code agent tooling with marketplaces, billing, and revenue intelligence so AI agents can be built, deployed and commercially sustained. By 2026 the “agent economy” has moved from experiments to production: teams need end-to-end stacks that handle event chaining, lifecycle and memory management, monetization primitives (subscriptions, per-call pricing, revenue share), analytics and discoverability. Key categories include AI Agent Marketplaces (discovery, commerce and distribution), AI Tool Marketplaces (SDKs, CLIs and integrations for building agents) and Revenue Intelligence Tools (usage attribution, pricing analytics and payout orchestration). Representative tools illustrate different approaches: GPTConsole targets developers with an SDK, API, CLI and web interface plus infrastructure for event chaining, lifecycle management and memory to create and monetize production-ready agents; Tate-A-Tate provides a no-code drag‑and‑drop workflow for rapid agent design and publication without writing code; Constants focuses on creator-first monetization by bundling compact mini‑sites and digital products to capture expert-led revenues. Platforms such as OpenLedger x402 and their peers aim to standardize how agent outputs, API calls and transactions are attributed and settled. Practical priorities in 2026 include robust instrumentation, clear billing semantics, developer and creator onboarding paths (code and no-code), compliance and data ownership, and integrated revenue analytics. For teams choosing a stack, the trade-offs are between developer control and operational overhead, discoverability versus platform fees, and the depth of revenue insights required to scale autonomous revenue streams.