Stagehand by Browserbase

AI-powered browser automation SDK built on Playwright that uses LLMs to interpret natural language instructions for web actions, making browser agents resilient to DOM changes without brittle CSS selectors.

Evaluated Mar 06, 2026 (0d ago) vcurrent
Homepage ↗ Repo ↗ AI & Machine Learning ai browser-automation web-scraping agents llm playwright
⚙ Agent Friendliness
78
/ 100
Can an agent use this?
🔒 Security
82
/ 100
Is it safe for agents?
⚡ Reliability
75
/ 100
Does it work consistently?

Score Breakdown

⚙ Agent Friendliness

MCP Quality
78
Documentation
82
Error Messages
76
Auth Simplicity
85
Rate Limits
70

🔒 Security

TLS Enforcement
100
Auth Strength
80
Scope Granularity
70
Dep. Hygiene
82
Secret Handling
78

Browser sessions run in isolated sandboxes on Browserbase infrastructure. LLM provider credentials must be managed separately and are not stored by Stagehand.

⚡ Reliability

Uptime/SLA
80
Version Stability
75
Breaking Changes
72
Error Recovery
74
AF Security Reliability

Best When

Your browser automation targets sites with dynamic or frequently changing DOM structures where maintaining selector-based scripts is too costly.

Avoid When

You need to run thousands of browser sessions per hour with strict cost controls, since LLM calls per action make this expensive at scale.

Use Cases

  • Build web scraping agents that navigate dynamic SPAs using natural language action descriptions instead of fragile selectors
  • Automate form filling and multi-step web workflows where DOM structure changes frequently
  • Create QA testing agents that verify UI behavior by describing expected outcomes in plain English
  • Extract structured data from web pages with LLM-powered parsing into typed schemas
  • Orchestrate agentic browsing tasks where the agent decides which links to follow based on content

Not For

  • High-throughput scraping at scale where per-action LLM inference costs are prohibitive
  • Applications requiring fully offline or air-gapped browser automation
  • Simple deterministic automation where XPath/CSS selectors are stable and LLM overhead is unnecessary

Interface

REST API
No
GraphQL
No
gRPC
No
MCP Server
Yes
SDK
Yes
Webhooks
No

Authentication

Methods: api_key
OAuth: No Scopes: No

Browserbase API key required for cloud sessions. Local mode (using local browser) requires only your LLM provider API key (OpenAI or Anthropic).

Pricing

Model: usage_based
Free tier: Yes
Requires CC: No

Dual cost model: Browserbase charges for cloud browser infrastructure; LLM inference charges accrue separately with your OpenAI or Anthropic account.

Agent Metadata

Pagination
none
Idempotent
No
Retry Guidance
Documented

Known Gotchas

  • Each act() call incurs a full LLM round-trip; complex page interactions can become expensive quickly
  • LLM action interpretation can hallucinate element locations on very complex or unusual page layouts
  • Session state is lost if the Browserbase session times out mid-task without checkpoint/resume support
  • observe() calls to enumerate possible actions add extra latency and cost before taking any action
  • Anti-bot detection can still block cloud browser sessions even with Stagehand's stealth features

Alternatives

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Scores are editorial opinions as of 2026-03-06.

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