Lovable
Lovable is a Stockholm-based AI app builder ("vibe coding") platform that turns natural-language prompts into full-stack web applications. Founded in late 2023 by Anton Osika (CEO) and Fabian Hedin (CTO), Lovable grew out of the founders' open-source GPT Engineer project (originally a CLI codegen tool that crossed 50,000+ GitHub stars) and was relaunched as a commercial product targeting non-technical builders, product managers, designers, and founders. Users chat with Lovable's agent to scaffold React/Tailwind front-ends backed by a managed Postgres ("Lovable Cloud") and authentication layer; projects can sync to GitHub or GitLab, deploy to lovable.app subdomains or custom domains, and integrate with Supabase, Stripe/Paddle, Resend, Mailgun, AWS S3, BigQuery, and Snowflake. The platform's developer surface is intentionally small — there is no traditional REST/SDK developer API. Programmatic entry points are limited to the "Build with URL" pattern (passing a prompt via querystring/hash to https://lovable.dev/?autosubmit=true) and a hosted Model Context Protocol server at https://mcp.lovable.dev that lets AI clients (Claude, Cursor, Claude Code) create projects, message the building agent, inspect diffs, provision Postgres databases, and read analytics on behalf of an authenticated Lovable account. Lovable raised a $200M Series A (Accel) in July 2025 and a $330M Series B (CapitalG, Menlo Anthology) in December 2025 at a $6.6B valuation, with reported ARR growing from $100M (July 2025) to $400M+ (February 2026) and roughly 8 million users.
Index entry only — little beyond a description and a link, and nothing machine-readable enough for an agent to act on without a human reading the site first.
API Evangelist profiles Lovable the way a machine reads it — 4 machine-readable artifacts, pulled from the provider's own public surface and indexed so a developer, an analyst, or an AI agent can evaluate it against every other provider on the network.
Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. From those artifacts we compute the Kin Score — Lovable scores 14.4/100 (minimal), with a separate agent-readiness read of 12/100 (human only). The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.
Kin Score
This is the API Evangelist rating — a single, repeatable read computed from the artifacts on this page. Green fill is points earned; the red track is points possible, so every bar shows earned-versus-possible at a glance.
Kin Score
How this is scored →scored 2026-07-27 · rubric v0.5
How we profile Lovable
Each block below is one kind of artifact we hold for Lovable. For each we say what it is and why it earns a place in the profile, then list every one we've indexed — capped at two rows, scroll within the panel for the rest.
MCP Servers 1
Model Context Protocol servers expose these APIs directly to AI agents. We profile them because agent-native access is the fastest-growing way this provider's capabilities actually get used.
Model Context Protocol servers that expose these APIs to AI agents.
mcp.lovable.dev
MCP SERVERSecurity Posture 3
Authentication, domain security, vulnerability disclosure, and trust-center signals — the evidence that a provider takes security seriously enough to document it. We profile it because you can't govern what you can't see.
Authentication, domain security, vulnerability disclosure, and trust-center signals.
Resources
Every other property we hold for Lovable — documentation, portals, status pages, policies, and corporate surface — grouped by the job it does, following the integrator's arc from getting started to running in production.
Documentation 2
Reference material describing how the API behaves
Agent Surfaces 1
MCP servers, agent skills, and machine-readable catalogs
Build 3
SDKs, sample code, and the tooling you integrate with
Access & Security 3
Authentication, authorization, and security posture
Learn 1
Tutorials, courses, talks, and written guidance
Operate 1
Status, limits, changes, and where to get help
Commercial 1
Pricing, plans, and the legal terms of use
Company 4
The organization behind the API
Other 4
Properties that don't map to a standard resource type
← All providers · Data indexed from github.com/api-evangelist/lovable-dev · machine-readable index on apis.io