alphalabs-intelligence
Live trading-pipeline intelligence for AI agents: signal scoring, calibration, recorded outcomes.
我該用這個嗎
品質與安全性
發現項目（1）
- LOWTool 'alphalabs_explain_decision' description lacks action verb在 alphalabs_explain_decision 中
根據工具定義與協定合規性的自動化分析。
上下文成本
這是每次將伺服器的工具載入模型上下文時所消耗的約略 token 數量。數量越高，可用於其他工作的注意力就越少。
安裝
一鍵安裝
將以下內容加入你的 `claude_desktop_config.json` 檔案：
{
"mcpServers": {
"alphalabs-intelligence": {
"url": "https://api.pak-labs.com/mcp"
}
}
}遠端端點
https://api.pak-labs.com/mcpstreamable-http它能做什麼
工具清單
工具（6）
🟢alphalabs_get_catalog
Free: list AlphaLabs Intelligence products, prices, and auth model.
輸入結構描述
{
"type": "object",
"properties": {},
"additionalProperties": false
}⚪alphalabs_calibration_report
Live paper-trading pipeline calibration telemetry: stage funnel, gate failures, near-misses. Derived analytics only — no positions, orders, or account data exist on this surface.
輸入結構描述
{
"type": "object",
"properties": {},
"additionalProperties": false
}🟢alphalabs_evaluate_signal(ticker, bias, confidence, catalyst, thesis, ...)
Score YOUR trade idea through the live AlphaLabs deterministic engine: composite score, tier, per-component sub-signals, floors. Price/volume confirmation is not evaluated (no vendor market data). Returns an evaluation_id for alphalabs_explain_decision.
輸入結構描述
{
"type": "object",
"properties": {
"ticker": {
"type": "string",
"description": "Symbol, e.g. NVDA"
},
"bias": {
"type": "string",
"enum": [
"bullish",
"bearish",
"neutral"
]
},
"confidence": {
"type": "number",
"minimum": 0,
"maximum": 1,
"description": "Your own conviction 0-1 (echoed, not scored)"
},
"catalyst": {
"type": "string",
"description": "What just happened (headline/event)"
},
"thesis": {
"type": "string",
"description": "Why it should move the stock"
},
"catalyst_type": {
"type": "string",
"description": "Optional label, e.g. 'Government Contract'"
},
"catalyst_score": {
"type": "number",
"minimum": 0,
"maximum": 100,
"description": "Optional 0-100 materiality if you scored it"
}
},
"required": [
"ticker",
"bias"
],
"additionalProperties": false
}⚪alphalabs_outcome_report
Recorded outcomes of the live pipeline's own decisions: hit rates, score-band tables, accepted-vs-rejected edge, gate near-miss regret. Aggregated engine telemetry — percent moves and counts only.
輸入結構描述
{
"type": "object",
"properties": {},
"additionalProperties": false
}⚪alphalabs_feature_attribution
Which engine inputs actually predict outcomes, measured on recorded live results: Spearman rankings, median-split deltas, dead inputs.
輸入結構描述
{
"type": "object",
"properties": {},
"additionalProperties": false
}🟢alphalabs_explain_decision(evaluation_id)
Glass-box breakdown of a prior evaluation by evaluation_id: every sub-signal, weight, floor, and the composite reasoning.
輸入結構描述
{
"type": "object",
"properties": {
"evaluation_id": {
"type": "string"
}
},
"required": [
"evaluation_id"
],
"additionalProperties": false
}社群
證據