Lightpanda vs OpenShell
Two of the top sandboxes, side by side: score, setup, license, activity and what each review found.
Lightpanda
Headless browser written in Zig for AI agents and scraping
OpenShell
Policy-enforced sandbox runtime for autonomous agents with credential brokering
| What we compare | Lightpanda | OpenShell |
|---|---|---|
| Score parts, out of 100 | ||
| Adoption | 85, widely used | 44, known |
| Freshness | 100, active | 100, active |
| Maintenance | 92, healthy | 88, healthy |
| Easy to run | 50, easy | 50, easy |
| Agent-ready | 70, partly | 85, ready |
| Facts from GitHub and the README | ||
| Stars | 36.3k | 15.8k |
| License | AGPL-3.0 (copyleft) | Apache-2.0 (permissive) |
| Last commit | Oct 2026 | Oct 2026 |
| Last release | Oct 2026 | Oct 2026 |
| Language | Zig | Not stated |
| Docker | Yes | Yes |
| GPU | Not needed | Not needed |
| arm64 or Apple Silicon | Mentioned | Mentioned |
Lightpanda
Lightpanda is a headless browser written in Zig, built on V8 for JavaScript, libcurl for HTTP and html5ever for parsing, with no graphical rendering. It exposes a CDP server on port 9222 for Puppeteer and Playwright, plus WebDriver BiDi, an MCP server, and a built-in LLM agent mode. It can also dump pages as HTML, Markdown, PNG or PDF from the command line.
Who it is for: Engineers running browser automation or web-browsing agents at scale
Strengths
- README benchmark: 123MB peak vs 2GB for headless Chrome over 100 pages
- CDP server works with Puppeteer; WebDriver BiDi also supported
- MCP server over stdio or HTTP, with isolated or shared sessions
- Agent output saved as replayable JavaScript scripts that need no LLM at runtime
Weaknesses
- No native Windows build; WSL2 required
- Linux binaries need glibc; they fail on Alpine/musl
- Telemetry is on by default; opt out via environment variable
- Not a full browser: no graphical rendering, partial Web Platform Tests coverage
- no GPU
- Docker
- Models: Anthropic, OpenAI, Gemini, Vertex AI, Mistral
- port 9222
OpenShell
Runs each agent in a sandbox with kernel-enforced limits on file access and system calls; every outbound connection passes a policy check, and agents never see real credentials, which a gateway injects only for approved endpoints. Policy changes are checked with formal verification before approval. Installs via a shell script on Linux, Apple Silicon macOS or WSL 2; Helm for Kubernetes; SDKs for Python, TypeScript, Go and Rust.
Who it is for: Platform teams running fleets of autonomous agents
Strengths
- Credentials attached by the gateway only to approved endpoints; sandboxes never hold them
- Formal verification flags risky new access before a policy change is applied
- Kubernetes deployment via Helm; GPU use inside sandboxes documented
- Python, TypeScript, Go and Rust SDKs plus agent skills via npx skills add
Weaknesses
- Windows support is WSL 2 only and experimental
- Default sandbox image is minimal Ubuntu with no agent; running one follows the docs walkthrough
- Anonymous telemetry on by default; disable with OPENSHELL_TELEMETRY_ENABLED=false
- Kubernetes installs require a CNI that enforces NetworkPolicy
- no GPU
- Docker + Compose
- Needs Docker, Podman or host virtualization
- Models: any provider via routed inference credentials