WebHive

WebHive appears to be an AI-driven browser automation/control center. It runs a local web UI and a controllable browser session (optionally reusing an existing Chrome profile) to let an AI model perform tasks in the browser while showing interactions via a built-in VNC/noVNC viewer. It supports multiple LLM providers via API keys configured in an .env file.

Evaluated Apr 04, 2026 (16d ago)
Homepage ↗ Repo ↗ Automation ai-ml browser-automation agents python self-hosted playwright vnc computer-use llm-integration
⚙ Agent Friendliness
28
/ 100
Can an agent use this?
🔒 Security
26
/ 100
Is it safe for agents?
⚡ Reliability
15
/ 100
Does it work consistently?

Score Breakdown

⚙ Agent Friendliness

MCP Quality
0
Documentation
45
Error Messages
0
Auth Simplicity
80
Rate Limits
0

🔒 Security

TLS Enforcement
20
Auth Strength
30
Scope Granularity
0
Dep. Hygiene
30
Secret Handling
50

The system is configured via environment variables for upstream LLM API keys, which is a good baseline. However, there is no information about transport security for the local web UI (README shows http://localhost), no described authentication/authorization for the UI/VNC endpoints, and no documented guidance on securely handling or minimizing browser profile credentials. If persistent sessions are enabled, sensitive cookies/logins may be retained on disk and accessible to the automation environment.

⚡ Reliability

Uptime/SLA
0
Version Stability
25
Breaking Changes
20
Error Recovery
15
AF Security Reliability

Best When

You want local, self-hosted AI browser automation with optional persistent browser state for interactive browsing.

Avoid When

You cannot provide LLM API keys or you need a documented public API/contract for programmatic integration; also avoid when you cannot control exposure of browser profile data and session credentials.

Use Cases

  • Automating multi-step web tasks via an AI model (form filling, navigation, browsing-based research)
  • Running agent-like browser workflows locally with access to a persistent browser session
  • Watching or debugging AI-driven browser interactions using VNC/noVNC video/streaming
  • Using existing Chrome/Firefox/Edge profile logins for authenticated browsing

Not For

  • Production-grade, headless, multi-tenant automation service without additional hardening
  • Use cases requiring fine-grained API-level access control and auditable service-to-service permissions
  • Tasks that require strict compliance boundaries without data-handling documentation

Interface

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

Authentication

Methods: LLM provider API keys via .env (OPENAI_API_KEY, ANTHROPIC_API_KEY, GOOGLE_API_KEY)
OAuth: No Scopes: No

Authentication is primarily via upstream model API keys configured in the local environment. The README does not describe any authentication mechanism for the local web UI itself (e.g., login/auth middleware) or for accessing the VNC/noVNC endpoints.

Pricing

Free tier: No
Requires CC: No

Project pricing is not described in the provided content; LLM usage cost depends on configured providers and usage.

Agent Metadata

Pagination
none
Idempotent
False
Retry Guidance
Not documented

Known Gotchas

  • No documented API/MCP interface for agents; integration would likely be via running the app and automating the UI/browser workflow rather than calling a stable programmatic contract.
  • If using persistent sessions and existing browser profiles, agent actions may depend on prior state (logins, cookies) and can cause unintended side effects.
  • VNC password defaults and browser-accessible UI endpoints may be exposed if the host is not properly firewalled (no guidance shown here).

Alternatives

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Scores are editorial opinions as of 2026-04-04.

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