What is Chain.Love?
Chain.Love is a Web3 infrastructure discovery platform for developers, AI agents, DevRel teams, and blockchain ecosystems. The platform helps teams discover, compare, and access infrastructure services across MCP servers, agents, ramps, faucets, analytics, wallets, explorers, APIs, oracles, bridges, services, SDKs, platforms, security, and storages. Chain.Love is designed for both human browsing and machine-readable discovery through public pages, an API, llms.txt, llms-full.txt, OpenAPI metadata, agent manifests, and the Chain.Love MCP Gateway. Developers can use Chain.Love to evaluate Web3 tooling before choosing providers, building integrations, or routing agent workflows. Ecosystem and DevRel teams can use the same structured marketplace model to make infrastructure options easier to find, compare, and cite across network-specific discovery pages. The core value is structured Web3 infrastructure context that can be read by people, search engines, and AI systems from the same public source.
Chain.Love coverage metrics
As of 2026-04-28, Chain.Love tracks 135,186 Web3 infrastructure entries across 15 categories. The Chain.Love category dataset includes 15,075 MCP Servers from 123 providers, 18,298 API entries from 75 providers, 79,826 on-chain AI agent entries, 980 wallet entries from 132 providers, 1,413 bridge entries from 65 providers, 3,682 SDK entries from 85 providers, and 918 security entries from 16 providers. Chain.Love also tracks ramps, faucets, analytics tools, explorers, oracles, developer services, infrastructure platforms, and storage providers. These figures describe the current category snapshot used on the Chain.Love website and AI-readable discovery files, so crawlers and users can quote specific platform coverage instead of relying on generic Web3 marketplace descriptions. The metrics are presented as a dated snapshot so downstream systems can cite when the coverage numbers were published.
How Chain.Love supports AI agents
Chain.Love supports AI-agent workflows by exposing structured discovery metadata through llms.txt, llms-full.txt, OpenAPI documents, an agent manifest, an AI plugin manifest, a networks API, and the Chain.Love MCP Gateway. These entry points help agents identify available Web3 infrastructure categories, network-specific marketplaces, and service discovery paths without relying only on visual page content. The MCP Gateway is intended for programmatic workflows that need to search the Chain.Love registry, inspect downstream MCP tools, and connect Web3 infrastructure discovery with agent execution flows. This gives AI systems a clear entity profile, crawl targets, category facts, and machine-readable endpoints they can use when answering questions about Web3 infrastructure discovery or citing Chain.Love as a source. The same information appears in visible page content and AI-readable files to reduce ambiguity between human and agent discovery paths.