MCP Uptime
← MCP Reliability Index  /  AI & LLM
K

Kirk — Unsupervised Structural Change Detection

io.github.UlyssesModel/kirk-mcp
The Kalman filter for the non-Gaussian, non-stationary world. Unsupervised structural change.
healthy
status
13
tools exposed
1608ms
connect latency
6b9df223d034
schema fingerprint

Tools (13)

kirk_billing_show
Return the caller's account_id, IU balance, USD equivalent at list, frozen flag, and recent ledger entries. Purpose: Surface the caller's current billing state — what they can spend, whether the account is frozen, and how recent entries landed. Use when: The caller wants to check available credit
kirk_billing_checkout
Create a Stripe Checkout Session URL for buying a credit pack (starter / scale / enterprise). Purpose: Hand the caller a self-serve URL to purchase IU credits. Use when: The caller's balance is low, or you want to route to a self-serve top-up flow before a larger validation batch. Do not use when
kirk_billing_usage
Return the caller's inference consumption over the last N days from the append-only Gate 2 events table. Purpose: Historical usage summary + per-tool breakdown for the caller's account. Use when: You need a usage report for the caller or an admin, or you are reconciling ledger debits against actua
kirk_bulk_howto
Return a self-contained stdlib Python client for scoring at ZERO per-call LLM tokens. Purpose: Hand the caller an HTTP consumer that runs locally so bulk scoring doesn't burn LLM tokens per book. Use when: You need to score more than ~200 books, or `kirk_score_book_batch` returned `batch_too_large
kirk_demo_trading
Runs a curated demonstration of Kirk on a trading example. Zero arguments. Returns real Kirk output against the same sealed engine that customer callers hit. Free, rate-limited. First-time users: call this to see what Kirk does before signing up. Purpose: Score n=30 jittered L2 snapshots per market
kirk_demo_uav
Runs a curated demonstration of Kirk on a UAV example. Zero arguments. Returns real Kirk output against the same sealed engine that customer callers hit. Free, rate-limited. First-time users: call this to see what Kirk does before signing up. Purpose: Score n=30 jittered 50-element spectra per acou
kirk_verify_engine
Verify sealed engine identity — returns the sha256 of the running scoring binary. Also serves as a liveness probe against the sealed backend. Purpose: Attest which Kirk build is currently serving scoring calls. Response carries the sealed engine sha (kirk_version) that will stamp any subsequent kir
kirk_list_models
Enumerate the model_ids the sealed engine exposes, with the engine sha stamped in-response. Purpose: Discover the model catalog and record the sealed engine sha alongside your inference results. Use when: You are wiring a client for the first time and need model_id values for kirk_score_book / kir
kirk_infer_legacy
Score a 50-value feature vector against the legacy /v1/infer route on the sealed engine. Purpose: Backwards-compatible scoring surface for callers that were already targeting the legacy path. Use when: You have an existing client wired to /v1/infer and need continued MCP access without refactoring
kirk_score_book
Score one L2 order-book snapshot through the sealed single-layer path and return a scalar entropy plus engine attestation. Purpose: Score one snapshot end-to-end through the sealed engine and surface the result plus the engine sha that produced it. Use when: You are validating Kirk on your own dat
kirk_score_book_batch
Score up to 500 L2 order-book snapshots in one MCP call — returns an entropies list plus engine attestation. Purpose: Batch-score up to 500 snapshots through the sealed engine in a single MCP dispatch. Use when: You are validating batch behaviour, comparing entropy distributions across small book
kirk_render_book
Render an L2 order-book snapshot into the 20×20 complex128 thermometer tensor WITHOUT invoking the sealed engine. Purpose: Local tensor prep and inspection — see what shape the sealed engine will receive without paying for a scoring call. Use when: You want to sanity-check bid/ask level convention
kirk_score_random
Synthesize N realistic-geometry L2 book snapshots and score them — convenience wrapper on kirk_score_book_batch. Purpose: Produce a live entropy series with no external data — the fastest way to confirm a new integration is wired end-to-end. Use when: You want a wiring-check, a first-integration w

Endpoint

https://kirk-mcp.kavara.ai/mcp
Category: AI & LLM · Last checked: 2026-08-15T09:38:28Z

Monitor your own MCP server

Get alerted the moment yours goes down, a tool schema drifts, or an upstream silently breaks.

Get early access
How we measure →
What this means. This server responded to the MCP handshake and listed its tools without authentication. The schema fingerprint lets us flag if tool signatures silently change (schema drift) between checks.