mcp server
alphalabs-intelligence
Live trading-pipeline intelligence for AI agents: signal scoring, calibration, recorded outcomes.
Description as published by the maintainer. Source
- version 1.0.0
- active
- evaluation
active — Registry entry last updated 2026-07-19. Dashed tags are derived by ZBS Index from the published description, not stated by the maintainer.
What this server can do
6 functions, named and described by the server itself. Parameter names are shown because they say more about what a function does than its name usually does.
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.
alphalabs_evaluate_signal(bias, thesis, ticker, catalyst, confidence, catalyst_type, catalyst_score)- 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. Required: ticker, bias.
alphalabs_explain_decision(evaluation_id)- Glass-box breakdown of a prior evaluation by evaluation_id: every sub-signal, weight, floor, and the composite reasoning. Required: evaluation_id.
alphalabs_feature_attribution- Which engine inputs actually predict outcomes, measured on recorded live results: Spearman rankings, median-split deltas, dead inputs.
alphalabs_get_catalog- Free: list AlphaLabs Intelligence products, prices, and auth model.
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.
Last successful function declaration observed on . Source: https://api.pak-labs.com/mcp. We list what the server declared; we do not call any of these functions.
Endpoint status observed on . Source: https://api.pak-labs.com/mcp.
Signals
These are separate measurements of different things. They are deliberately not combined into one score, because a popularity number that mixes website traffic with saves and stars cannot be checked or acted on.
| Signal | Value | What it measures | Window | Observed | Source |
|---|---|---|---|---|---|
| Latest published version | 1.0.0 | Latest version string the maintainer published to the registry. | as of fetch | Model Context Protocol | |
| Registry record last updated | 2026-07-19 | When the registry record was last updated by its maintainer. | point in time | Model Context Protocol | |
| First listed in the MCP Registry | 2026-07-19 | Date this server was first published to the official MCP Registry. Not a usage or quality measure. | point in time | Model Context Protocol | |
| mcp tools declared | 6 tools | Number of functions the server itself declared when asked to list them. This is what the server offers an agent, not a measure of how well any of them work. | as of probe | api.pak-labs.com | |
| mcp endpoint status | ok | The server listed 6 functions when asked. | as of probe | api.pak-labs.com |
Where to get it
This record as data
Every field on this page, with its source and observation date, is in the catalog JSON. Fetch the whole kind at once instead of parsing this HTML.
GET /api/v1/entries/mcp_server.json