How does lychee fit into CI/CD pipelines and large projects?

lychee is a fast, async link checker written in Rust, and it fits CI/CD pipelines and large projects in two concrete ways: it is built for speed on large codebases, and it emits structured JSON output that automation can consume. If your project has many Markdown or HTML files and you want broken hyperlinks and mail addresses caught automatically, lychee is designed for that job. The sections below cover what it checks, how the async design helps at scale, and how to wire the JSON output into a pipeline.

What lychee checks

lychee natively supports Markdown and HTML files, which makes it a direct fit for documentation sites and web projects. It finds broken hyperlinks and mail addresses. If your repository is mostly docs, README files, or generated HTML, you can point lychee at those files without a conversion step.

Why the async, Rust-based design matters for large projects

The site describes lychee as "built with Rust and designed for speed, making it perfect for large projects." Two properties follow from that:

• Async checking means link requests are not processed one at a time, so a large set of URLs does not serialize into a long wait.
• A single static binary means installation and updates do not pull in a runtime or dependency tree, which keeps CI images and local setups simple.

For a large project, the practical effect is that a full link sweep can run as a routine step rather than a slow, occasional audit.

Integrating lychee into CI/CD

The documented integration path is structured JSON output: the site states you can "easily integrate lychee into your CI/CD pipelines with structured JSON output." That gives you a machine-readable result to act on instead of parsing human-readable logs.

A typical pipeline shape:

1. Trigger — run on pull requests, on a schedule, or before deploy, depending on how often links change.
2. Run lychee against your Markdown/HTML targets.
3. Consume JSON output — fail the job on broken links, or post the results as a comment/artifact.
4. Verify — confirm the job fails when you introduce a deliberately broken link, so you know the gate actually works.

Common sticking points

• Network-dependent checks: link checking reaches external hosts, so CI runners need outbound access and results can vary with transient failures. Decide whether external failures should block a merge or only warn.
• Scope: point lychee at the files you actually care about (docs, site output) rather than the whole repository, to keep runs focused.
• Output handling: since JSON is the integration surface, make sure your pipeline step captures stdout correctly and parses it rather than grepping logs.

Where it fits best

Getting started

The site offers a "Get started" path and a GitHub repository for installation and usage details. Start by running lychee locally against your docs to see the baseline, then move the same command into CI and switch your pipeline logic to the JSON output.