Loading comparison...
Both record browser interactions to create reusable automations. DataFaucet captures API traffic and outputs MCP servers. Retriever AI records full browser flows and replays them deterministically with zero token cost. Different layers of the stack.
| Capability | DataFaucet | Retriever AI |
|---|---|---|
| Primary purpose | ✓Generate hosted MCP servers from API traffic | ~Record browser tasks as deterministic subroutines |
| Output format | ✓Hosted MCP server (SSE, JSON-RPC) | ~Replayable subroutine (proprietary format) |
| What gets captured | ~API traffic (XHR/fetch calls) | ✓Full browser interaction (clicks, typing, navigation) |
| MCP compatibility | ✓Native (standard MCP protocol) | ✗No (proposes separate A2W protocol) |
| Execution model | ✓API call replay with parameter substitution | ✓Deterministic browser replay (zero tokens) |
| Token cost per call | ~Minimal (structured tool call + response) | ✓Zero (replay is pre-recorded, no LLM needed) |
| Works with any MCP client | ✓Yes (Claude, Cursor, Windsurf, Codex) | ✗No (Retriever platform only) |
| Handles dynamic content | ✓Yes (parameterized API calls) | ~Limited (replay follows exact recorded path) |
| Setup approach | ✓Browse URL, capture traffic, deploy | ✓Record task once, save as subroutine |
| Hosting | ✓Fully managed cloud endpoint | ✓Retriever cloud platform |
| Fragility to UI changes | ✓Low (captures API layer, not DOM) | ~Higher (replays DOM interactions) |
| Multi-step workflows | ~Multiple tools composed by agent | ✓Single recorded flow (multi-step built in) |
Want your AI agents to call APIs, not replay browser clicks?
DataFaucet captures at the API layer. More resilient to UI changes, works with any MCP client.
Retriever AI records exactly what happens in the browser: clicks, keystrokes, page transitions. When you replay a subroutine, it executes the same DOM interactions deterministically without involving an LLM. Zero tokens consumed per execution. The trade-off is fragility: if the target app changes its UI layout, recorded flows break.
DataFaucet captures one layer deeper: the API calls the web app makes. When a button click triggers a POST to /api/orders, DataFaucet records that POST with its parameters. The output is a typed MCP tool that any agent can invoke with different arguments. UI redesigns don't break API-level tools unless the backend API itself changes.
They solve different problems. Retriever excels at full end-to-end flows where the exact UI interaction matters (filling forms, navigating wizards, multi-page workflows). DataFaucet excels at giving AI agents programmatic API access that composes flexibly across different use cases.
Watch DataFaucet capture endpoints and deploy a working server. Takes 60 seconds.
Free tier. 3 servers. No credit card required.