Autonomous agents increasingly interact with the web, yet most websites remain designed for human browsers -- a fundamental mismatch that the emerging ``Agentic Web'' must resolve. Agents must repeatedly browse pages, inspect DOMs, and reverse-engineer callable routes -- a process that is slow, brittle, and redundantly repeated across agents. We observe that every modern website already exposes internal APIs (sometimes called shadow APIs) behind its user interface -- first-party endpoints that power the site's own functionality. We present Unbrowse, a shared route graph that transforms browser-based route discovery into a collectively maintained index of these callable first-party interfaces. The system passively learns routes from real browsing traffic and serves cached routes via direct API calls. In a single-host live-web benchmark of equivalent information-retrieval tasks across 94 domains, fully warmed cached execution averaged 950,ms versus 3{,}404,ms for Playwright browser automation (3.6× mean speedup, 5.4× median), with well-cached routes completing in under 100,ms. A three-path execution model -- local cache, shared graph, or browser fallback -- ensures the system is voluntary and self-correcting. A three-tier micropayment model via the x402 protocol charges per-query search fees for graph lookups (Tier3), a one-time install fee for discovery documentation (Tier1), and optional per-execution fees for site owners who opt in (Tier~2). All tiers are grounded in a necessary condition for rational adoption: an agent uses the shared graph only when the total fee is lower than the expected cost of browser rediscovery.
Figures & tables
Rapid-
Post-
Un-
Property
API
man
browse
Coverage
Official
Official
Any site
Discovery
Manual
Manual
Passive
Internal APIs
×
×
✓
Agent-native
Partial
×
✓
Table 1: Qualitative comparison with existing API aggregation platforms.
Figure 1: Three-path execution model. The orchestrator routes requests to the local cache, shared graph (x402 payment), or browser fallback. Discovered routes are published back (dashed).
Domain
Task
Output
Wikipedia
Article summary for topic
JSON: title, extract
GitHub
Repository star count
JSON: stars, forks
Hacker News
Top 5 front page items
JSON: array of titles
Weather
Current conditions for city
JSON: temp, humidity
Table 2: Representative benchmark tasks with output format.
Metric
Unbrowse
Playwright
Domains tested
94
Cache hits
94 / 94
Mean latency
950 ms
3,404 ms
95% CI
(870–1,030)
(3,180–3,630)
Median latency
630 ms
3,402 ms
IQR
210–1,480 ms
2,100–4,600 ms
Table 3: Warmed-cache performance across 94 domains. Both paths run three times; third pass measured.
Figure 2: Distribution of speedup ratios (Playwright latency / Unbrowse latency) across 94 domains. The majority of domains cluster between 3–9 × speedup, with a right tail extending to 30 × for domains whose APIs return JSON in under 100 ms but whose rendered pages require 2–4 seconds of JavaScript execution. Dashed lines indicate mean and median speedup. Raw data available in the benchmark repository.
Table 5: Estimated per-task cost comparison. 4 4 4 LLM token costs assumed: 15/1Minput,75/1M output (Claude Opus 4, March 2026). These figures are illustrative; actual costs vary by provider and change frequently. Tier 1 install fees and Tier 3 search fees are based on dynamic pricing at time of writing. Tier 2 per-execution fees are set by site owners and shown as illustrative ranges.
National Key Laboratory for Novel Software Technology, Nanjing University, China · School of Artificial Intelligence, Nanjing University, China · Fellou AI