Agentery pricing intelligence · Agent profile · TradingAgents
Agent profile · independently tracked by Agentery
TradingAgents
simulates a professional trading firm using multiple specialized LLM agents (analysts, researchers, traders, risk managers) to make stock trading decisions
Agentery price verdictNo pricing observed
Billing model—
Last checked28 Jul 2026pricing & liveness
What it does
The specific capability behind this listing, and where to get it.
TradingAgents
simulates a professional trading firm using multiple specialized LLM agents (analysts, researchers, traders, risk managers) to make stock trading decisions
historical stock prices, news articles, social media sentiments, insider transactions, financial reports, and technical indicators → analysis reports, trading decision signals with rationales, buy/sell orders, and portfolio adjustments
autonomy: agentic
Official TradingAgents links
Price status · observed daily
No public commercial pricing observed.
No price does not imply the product is free. Any code-host platform pricing is excluded.
Is TradingAgents good value?
Price is straightforward; the useful comparison is capability, compatibility and operational cost.
No price benchmark
No public commercial pricing observed.
Agentery has not observed a public price for this provider. No price does not mean free.
Observed commercial pricenone
NicheAlgorithmic Trading Bot
Price benchmarknot applicable
What to compare instead
Check capability before deciding
Compare capability, compatibility and operational cost against comparable providers — Agentery keeps the price status explicit and never invents a verdict.
View the full niche →Comparable Algorithmic Trading Bot
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See the MCP response behind this page · get_agent_profile()
See the MCP response behind this pageget_agent_profile
{
"agent_id": "tradingagents",
"name": "TradingAgents",
"url": "https://tradingagents-ai.github.io/",
"logo": "https://agentery.com/logos/CP-Y8TR2R-ld256.png",
"niche": "algorithmic-trading-bot",
"category": "financial-services",
"short_summary": "simulates a professional trading firm using multiple specialized LLM agents (analysts, researchers, traders, risk managers) to make stock trading decisions",
"task_performed": "simulates a professional trading firm using multiple specialized LLM agents (analysts, researchers, traders, risk managers) to make stock trading decisions",
"inputs_accepted": [
"historical stock prices",
"news articles",
"social media sentiments",
"insider transactions",
"financial reports",
"and technical indicators"
],
"outputs_produced": [
"analysis reports",
"trading decision signals with rationales",
"buy/sell orders",
"and portfolio adjustments"
],
"integrations_available": [],
"protocols_or_interfaces": [],
"industry_fit": [
"finance"
],
"autonomy_level": "agentic",
"human_approval_needed": "unclear",
"pricing_model": "unclear",
"price": {
"observed": false,
"billing": "not_found",
"currency": null,
"lowest_monthly_usd": null,
"monthly_usd": null,
"headline": "No public price found",
"summary": "No public price found on the vendor site.",
"confidence": "high",
"source_url": "https://tradingagents-ai.github.io/",
"checked_at": "2026-07-26T10:10:03.509Z",
"amount": null,
"display": null,
"plans": [],
"source": "render+llm"
},
"trust_or_rating_signal": [
"academic paper from UCLA and MIT researchers",
"published experimental performance metrics vs baselines",
"code repository"
],
"evidence_quality": "medium",
"entity_type": "agent",
"regulated_data_suitability": "unclear",
"evidence_urls": [
"https://tradingagents-ai.github.io/"
],
"last_checked": "2026-06-16",
"how_to_connect": {
"website": "https://tradingagents-ai.github.io/",
"docs": null,
"mcp": null,
"a2a": null,
"api": null,
"protocols": []
},
"liveness": {
"probed": true,
"alive": true,
"endpoint_kind": "site",
"latency_ms": 872,
"uptime_7d": 1,
"checked_at": "2026-07-28T02:39:02.639Z",
"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."
}