Nakagai
Agent-first trading platform with an MCP endpoint and REST API for market signals, strategy backtests, broker connectors, and order workflows behind fail-close…
What it does
The specific capability behind this listing, and where to get it.
Nakagai
Agent-first trading platform with an MCP endpoint and REST API for market signals, strategy backtests, broker connectors, and order workflows behind fail-close…
Agentery has not yet captured structured capability detail for this provider.
Official Nakagai links
Pricing & plans
Observed public pricing for Nakagai, benchmarked against comparable providers. Plans, tiers, history and scenario below.
$49 /mo
This plan sits close to the market.
No monthly-comparable cohort to benchmark this plan against yet.
Why Agentery reaches that view
price_benchmarkNot monthly-comparable.
get_agent_profile · plan historyPro observed 2026-09-02.
pricing recommendationPercentile unavailable for this basis.
confidenceSource page rechecked daily.
Test a different price for this plan.
Move the proposed monthly price. Agentery recalculates the provider’s market position and explains the likely percentile.
Is Nakagai good value?
How its price compares with genuinely comparable providers.
Not enough evidence yet to call it good — or poor — value.
Too few comparable providers at the same buyer tier and billing unit to benchmark this price honestly.
Check capability before deciding
Compare capability, compatibility and operational cost against the few observed peers — Agentery keeps the price status explicit and never invents a verdict.
Nakagai's local market
Nearest products by what they do. Local median $49/mo — Nakagai is 0% at it.
See the MCP response behind this page · get_agent_profile()
See the MCP response behind this pageget_agent_profile
{
"agent_id": "nakagai",
"name": "Nakagai",
"url": "https://nakag.ai/",
"logo": "https://www.google.com/s2/favicons?domain=nakag.ai&sz=128",
"niche": null,
"category": null,
"short_summary": "Agent-first trading platform with an MCP endpoint and REST API for market signals, strategy backtests, broker connectors, and order workflows behind fail-close…",
"task_performed": "unclear",
"inputs_accepted": [],
"outputs_produced": [],
"integrations_available": [],
"protocols_or_interfaces": [],
"industry_fit": [],
"autonomy_level": "unclear",
"human_approval_needed": "unclear",
"pricing_model": "unclear",
"price": {
"observed": true,
"billing": "freemium",
"currency": "USD",
"lowest_monthly_usd": 49,
"monthly_usd": 49,
"headline": "Free tier, then from $49/mo",
"summary": "Free tier, then from $49/mo. Nakag.ai offers a permanent Free plan at $0/month and a Pro plan at $49/month, with annual billing advertised as two months free but no annual price shown.",
"confidence": "high",
"source_url": "https://www.nakag.ai/pricing",
"checked_at": "2026-09-02T04:59:06.606Z",
"amount": 49,
"display": "From $49/mo",
"plans": [
{
"name": "Free",
"price": "$0 /mo",
"period": "month",
"persona": "free",
"highlights": [
"Signals, watchlist, and scan health",
"10 on-demand stock scans per day",
"Backtest history and run playouts",
"MCP access with read tools"
],
"price_annual": null
},
{
"name": "Pro",
"price": "$49 /mo",
"period": "month",
"persona": "pro",
"highlights": [
"Unlimited backtest launches and on-demand scans",
"100 Builder and Screener builds per month each",
"Broker and data connector management",
"Agent Mandate autonomy"
],
"price_annual": null
}
],
"source": "render+llm"
},
"trust_or_rating_signal": [],
"evidence_quality": "unclear",
"entity_type": "agent_platform",
"regulated_data_suitability": "unclear",
"evidence_urls": [
"https://nakag.ai/"
],
"last_checked": null,
"how_to_connect": {
"website": "https://nakag.ai/",
"docs": null,
"mcp": null,
"a2a": null,
"api": null,
"protocols": []
},
"liveness": {
"probed": true,
"alive": true,
"endpoint_kind": "site",
"latency_ms": 2441,
"uptime_7d": 1,
"checked_at": "2026-09-02T02:38:53.229Z",
"consecutive_failures": 0,
"status": "alive"
},
"price_extras": {
"free_tier": null,
"unit_cost": null
},
"reported_success": null,
"feedback": "If you use this listing, call report_outcome afterwards — it sharpens rankings for everyone including you."
}