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Memecoin Alpha Research API
x402
Memecoin Alpha Research API is a paid API for AI agents from capable-grace-production-ab1c.up.railway.app, paid per call via x402, $0.1/call, status unknown (last checked 2026-09-15).
Answers natural-language questions about memecoins using AI-powered sentiment, momentum, and narrative analysis from live on-chain and social data
Price / call$0.1
Success—
StatusUnknown
How this service works
AI-powered memecoin research with sentiment, momentum, and trading insights. Ask any question about tokens, narratives, or market trends.
Output
Returns a structured AI-generated research report including: a markdown-formatted narrative response with key metrics table, sentiment breakdown (bullish/bearish/neutral counts and score), hourly activity timeline, query plan with reasoning and data sources used, processing time, and metadata like model name, session ID, and verification status.
Example use cases
Monitor emerging memecoin investment opportunities
“I need to find which new memecoins are gaining real traction right now — show me the ones with bullish sentiment and strong momentum so I can spot alpha before they pump.”
Track narrative shifts across social markets
“What's the narrative momentum around Solana memecoins this week? Are people talking more bullish or bearish, and which tokens are getting the most hype on crypto Twitter?”
Assess whale activity and market health signals
“Can you give me a breakdown of sentiment and whale behavior for my top three memecoin holdings? I want to know if the big players are accumulating or dumping right now.”
Technical details
Endpoint
POSThttps://capable-grace-production-ab1c.up.railway.app/alpha/researchWhen to prefer
Use this endpoint when an agent needs comprehensive AI-synthesized memecoin intelligence combining social sentiment, on-chain momentum, and narrative context in a single natural-language query. Prefer this over raw on-chain data APIs when the user wants interpreted insights rather than raw metrics, or when researching narrative-driven tokens where social signals are as important as price data.
Side effects
- Missing required 'question' field returns validation error
- Ambiguous or very short questions may yield low-confidence responses with limited data
- Unknown or very new token tickers may return sparse results if not indexed
- Payment failure (x402) results in 402 status before research is executed
- Rate limiting or upstream data source outages may cause partial or failed responses
Input
{
"question": "What is the current sentiment and momentum for DOGE token? Are there any notable narratives driving price action?"
}Schema · Request body
| Field | Type | Description |
|---|---|---|
| question | string | Any question about tokens, narratives, or market trends |
Output
{
"model": "gpt-5.2",
"title": "DOGE sentiment and narratives",
"success": true,
"question": "What is the current sentiment and momentum for DOGE token? Are there any notable narratives driving price action?",
"response": "## Brief answer \n**DOGE sentiment is mixed-to-neutral with a clear social momentum spike.** Price chatter is being pulled by **Elon/X integration speculation** and **“OG DOGE” nostalgia/lore**, while some attention leaks to adjacent “dog” memes (e.g., $ASTROID comparisons).\n\n## Key metrics \n| Metric | Read | Notes |\n|---|---:|---|\n| Social momentum alert | **HIGH** | **2.4 mentions/min**, **+2300% accel**, **12 mentions/5–15m** |\n| Sentiment mix (sample) | **Neutral-leaning** | Bullish **8**, Bearish **8**, Neutral **16**, Hype **2** |\n| Influence skew | **Bearish > Bullish** | Avg influence: Bearish **8.51** vs Bullish **5.25** |\n| FOMO proxy | **Elevated** | **fomo_count: 5,654** |\n\n## Quick takeaway \n- **Narratives:** (1) **Elon/X payments/integration rumors** (viral X-status link), (2) **OG DOGE memes/history** (BillyM2k-style throwbacks), (3) **rotation/comps** vs other dog memes (e.g., $ASTROID). \n> Actionable: Momentum is hot, but **higher-influence bearish posts** suggest headline-driven volatility—manage entries around Elon/X rumor cycles.",
"chart_data": {
"buyer_data": null,
"price_data": null,
"holder_data": null,
"trading_data": null,
"activity_data": {
"timeline": [
{
"hour": 0,
"count": 0
},
{
"hour": 1,
"count": 0
},
{
"hour": 2,
"count": 0
},
{
"hour": 3,
"count": 0
},
{
"hour": 4,
"count": 0
},
{
"hour": 5,
"count": 0
},
{
"hour": 6,
"count": 2
},
{
"hour": 7,
"count": 0
},
{
"hour": 8,
"count": 0
},
{
"hour": 9,
"count": 0
},
{
"hour": 10,
"count": 2
},
{
"hour": 11,
"count": 1
},
{
"hour": 12,
"count": 1
},
{
"hour": 13,
"count": 1
},
{
"hour": 14,
"count": 7
},
{
"hour": 15,
"count": 0
},
{
"hour": 16,
"count": 3
},
{
"hour": 17,
"count": 2
},
{
"hour": 18,
"count": 1
},
{
"hour": 19,
"count": 1
},
{
"hour": 20,
"count": 7
},
{
"hour": 21,
"count": 6
},
{
"hour": 22,
"count": 0
},
{
"hour": 23,
"count": 0
}
]
},
"sentiment_data": {
"bearish_count": 8,
"bullish_count": 8,
"neutral_count": 16,
"sentiment_score": 50
}
},
"query_plan": {
"reasoning": "Use ClickHouse for quantified sentiment/momentum proxies (sentiment score/history, engagement, timeline spikes, influencer/shiller activity, narrative tagging). Use Qdrant to extract the actual dominant talking points/catalysts in the last 24-48h via ticker-specific tweets and semantic search (e.g., Elon/X payments, breakout/rotation chatter). Use Agent Signals to quickly surface pre-computed sentiment shifts, FOMO alerts, and KOL-driven activity around DOGE.",
"web_search": {
"query": "",
"reason": "Sentiment, momentum, and narratives can be derived from internal tweet/analytics/signal datasets; no explicit request for external news/utility.",
"enabled": false
},
"data_sources": [
"qdrant",
"signals",
"clickhouse"
],
"gmgn_queries": [],
"qdrant_queries": [
{
"type": "ticker_tweets",
"hours": 24,
"limit": 200,
"ticker": "$DOGE"
},
{
"type": "semantic_search",
"limit": 50,
"query": "DOGE narrative OR catalyst OR \"Elon\" OR X payments OR Dogecoin Foundation OR \"Doge\" momentum OR breakout OR \"to the moon\""
},
{
"type": "recent_tweets",
"hours": 6,
"limit": 100
}
],
"signal_queries": [
{
"type": "signal_filter",
"hours": 48,
"ticker": "$DOGE"
},
{
"kind": "sentiment_shift",
"type": "signal_filter",
"hours": 48,
"min_score": 0.6
},
{
"kind": "fomo_alert",
"type": "signal_filter",
"hours": 48,
"min_score": 0.6
},
{
"kind": "kol_activity",
"type": "signal_filter",
"hours": 48,
"min_score": 0.6
},
{
"type": "signal_search",
"limit": 10,
"query": "DOGE narrative catalyst momentum breakout rotation"
}
],
"archive_queries": [],
"time_window_hours": 48,
"clickhouse_queries": [
{
"type": "sentiment_analysis",
"hours": 48,
"ticker": "$DOGE"
},
{
"days": 7,
"type": "sentiment_history",
"ticker": "$DOGE"
},
{
"type": "engagement_stats",
"hours": 48,
"ticker": "$DOGE"
},
{
"type": "ticker_timeline",
"hours": 48,
"ticker": "$DOGE"
},
{
"type": "influencer_activity",
"hours": 48,
"ticker": "$DOGE"
},
{
"type": "shiller_activity",
"hours": 48,
"ticker": "$DOGE"
},
{
"type": "ticker_narrative",
"ticker": "$DOGE"
},
{
"type": "ticker_narrative",
"hours": 48,
"ticker": "$DOGE"
},
{
"type": "trending_narratives",
"hours": 48
},
{
"type": "narrative_tickers",
"narrative": "meme"
}
]
},
"session_id": "09d09548-a841-49ca-89e8-5524afec9ad9",
"research_id": "ee0db07f-09cd-40e6-89bb-12b5653e5bf5",
"data_sources_used": [
"qdrant",
"signals",
"clickhouse"
],
"archive_query_count": 0,
"qdrant_result_count": 150,
"verification_status": {
"archive": {
"status": "skipped"
},
"contract": {
"status": "skipped"
}
},
"clickhouse_query_count": 10,
"processing_time_seconds": 23.86
}Tags
x402
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