MCP server

Alphaassay Official

com.alphaassay/mcp

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

Fail-closed backtest/signal validation: overfitting, leakage, deflated Sharpe. NOT financial advice.

Website

At a glance

Type

MCP server

Publisher

alphaassay.com (verified by the MCP Registry)

Status

Working at last check

Tools

21

Token cost

About 33,383 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http alphaassay https://mcp.alphaassay.com/mcp

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.alphaassay]
url = "https://mcp.alphaassay.com/mcp"

Gemini CLI

{"mcpServers":{"alphaassay":{"httpUrl":"https://mcp.alphaassay.com/mcp"}}}

Cursor

{"mcpServers":{"alphaassay":{"url":"https://mcp.alphaassay.com/mcp"}}}

VS Code

{"servers":{"alphaassay":{"type":"http","url":"https://mcp.alphaassay.com/mcp"}}}

Antigravity

agy mcp add alphaassay https://mcp.alphaassay.com/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"alphaassay","server_url":"https://mcp.alphaassay.com/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"alphaassay","server_url":"https://mcp.alphaassay.com/mcp"}

Tools

• assay_backtest ~2519 tokens
  Use this when you want a code-computed DSL backtest whose deflated- Sharpe verdict still means something after repeated searching -- every run is priced into your family's trial ledger. A research audit, not buy/sell advice. Ledger-aware DSL backtest with honest family-level trial accounting. Defin
• assay_batch ~2952 tokens
  Use this when you optimised over a grid and want to submit the WHOLE sweep honestly -- every variant a ledger trial the family budget prices, so selection bias cannot hide. A research audit, not buy/sell advice. Submit your WHOLE parameter sweep honestly -- one call, every variant a ledger trial. Y
• assay_calibration ~285 tokens
  Use this when you want to inspect AlphaAssay's current public calibration state for free rather than trust marketing. Calibration v0 is a population/status disclosure, not an outcome score or track record. Self-calibration of the validator's mature pre-registration population: the published contrac
• assay_certificate_verify ~582 tokens
  Use this when someone hands you a signed AlphaAssay certificate and you want to verify both its Ed25519 signature and current platform trust. A verification tool, not buy/sell advice. Verify a signed AlphaAssay certificate against externally rooted public trust. This hosted verifier evaluates full
• assay_conformal ~1317 tokens
  Use this when your model emits prediction intervals or confidence bands and you want to audit whether realised outcomes actually fall inside them at the claimed coverage -- a calibration audit, not advice. Does your model's confidence label survive contact with outcomes? Coverage audit over predicti
• assay_cpcv ~2664 tokens
  Use this when you have a return history and want the full combinatorial purged cross-validation (CPCV) distribution -- not one walk-forward number -- to see how path-dependent the edge really is. The FULL combinatorial purged CV distribution over your return history -- not one number, the whole pict
• assay_demo ~293 tokens
  Use this when you want to see AlphaAssay's exact verdict envelope -- schema, findings, leakage taxonomy -- on a built-in example before spending a check. A methodology audit; no buy/sell advice. Free demo verdict -- see AlphaAssay's full output shape in one call. Runs the real fail-closed validator
• assay_falsify ~2286 tokens
  Use this when you want your strategy actively attacked -- execution lag, cost stress, regime split, parameter neighbourhood, drift-burst -- to see what kills it first. Demote-only; it does not give buy/sell advice. We do not check your signal -- we actively try to KILL it. An adversary runs a batter
• assay_forensics ~1406 tokens
  Use this when a signal looks good but you suspect leakage or look-ahead and want to know WHY it fails, not just that it fails -- a diagnostic audit, it does not give buy/sell advice. Leakage forensics: WHY your signal fails, not just that it fails. Upload your own decision timestamps (symbol, decis
• assay_gauntlet ~3078 tokens
  Use this when you want the whole reality-check battery on a strategy in one call -- overfitting, leakage, costs, regimes and a matched-random placebo -- as a demote-only dossier, never buy/sell advice. The full reality-check battery in ONE call -- validator, family deflation, matched-random placebo,
• assay_graveyard ~551 tokens
  Use this when you want to check, for free, how often a signal family (e.g. sma_cross) has already been falsified and what usually kills it, before spending a check. Anonymised stats only -- no buy/sell advice. Free lookup: how often has this signal family already died? Anonymised falsification stat
• assay_pbo ~1112 tokens
  Use this when you have the T x N returns of a grid search and want the probability of backtest overfitting (PBO, CSCV) -- did the sweep find an edge or manufacture one? A demote-only audit, not buy/sell advice. Did your parameter sweep FIND an edge -- or manufacture one? PBO over the whole trial mat
• assay_preflight ~723 tokens
  Use this when you want to lint the SHAPE of a submission (DSL spec, candles or trades) for free before spending a check, so a typo never costs you one. A format check only -- it gives no buy/sell advice. Free payload lint -- fix your submission BEFORE spending a check. Validates the SHAPE of what y
• assay_provider_protocol ~429 tokens
  Use this when you want to judge ANY signal seller -- including us -- with a machine-readable seven-test falsification protocol you can run in an afternoon. It scores methodology, not markets: no buy/sell advice. Test ANY signal provider in an afternoon -- the falsification protocol as machine-readab
• assay_register ~2309 tokens
  Use this when you want to seal a strategy and its success criteria NOW, before the forward data exists, so that registration cannot be adapted or backfilled against those later bars -- a commitment audit, not buy/sell advice. Pre-register a signal NOW; freeze its terms before the forward evidence ex
• assay_reproduce ~2477 tokens
  Use this when someone hands you a claimed track record and you want to recompute it yourself from the fills and candles -- an arithmetic audit of the numbers, not buy/sell advice. Independently recompute a claimed track record -- audit the arithmetic, not the story. New audit object: not the signal
• assay_signal ~2939 tokens
  Use this when you have a backtest result or live track record (a trades log, equity curve or QuantConnect export) and need to know whether the edge is real or just overfitting, survivorship or luck. Validate a trading strategy export: fail-closed statistical verdict. Reality-check for backtest resu
• assay_survivors ~1110 tokens
  Use this when you ran a grid or parameter sweep and want to know WHICH variants survive family-wise error control (FWER) rather than surfacing by chance -- an error-budget disclosure, not buy/sell advice. WHICH variants of your sweep survive family-wise error control -- an error-budget disclosure, n
• assay_tradelog ~1257 tokens
  Use this when you have a raw fill or trade log and want it scanned for internal contradictions -- look-ahead timestamps, pnl that disagrees with the row's own prices, duplicate or out-of-order fills. Interrogate a raw fill log for internal contradictions -- no candles needed. assay_preflight lints
• assay_var_es ~1744 tokens
  Use this when you have VaR or Expected-Shortfall forecasts and need to know whether reality breached them more often or deeper than your claimed tail level allows -- a risk-forecast audit, not buy/sell advice. Does your risk model's VaR/ES forecast survive contact with reality? Exceedance backtest o
• assay_verdict ~1350 tokens
  Use this when a signal was pre-registered with assay_register and the maturity window has passed -- get the post-cutoff verdict computed only from data after registration. A sealed audit, it gives no buy/sell advice. Post-cutoff verdict under the registration's sealed terms. Evaluates a registratio

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