Kirk — Unsupervised Structural Change Detection
io.github.UlyssesModel/kirk-mcp · v1.0.2
The Kalman filter for the non-Gaussian, non-stationary world. Unsupervised structural change.
MCPremoteAPI keyAI & LLME-commerce
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Last check
Reachable, 14 tools, protocol 2025-06-18 · checked 2026-10-17
Test & rating
A 100/100
What it does: 14 tools · 13 read, 1 write · AI & LLM, CRM & sales, E-commerce
Test call kirk_billing_show: worked (1,287 ms)
How the rating is made
- Answers without login: +30
- Speed of first answer: +10
- Lists tools: +10
- Tool descriptions: +15
- Parameter descriptions: +10
- Read/write annotations: +5
- Safe test call: +20
- More than 80 tools: 0
Tested 2026-10-17. Fixed rules, no AI model. Grade A needs a successful real call.
Install
Remote URL
https://kirk-mcp.kavara.ai/mcpTools
14 tools listed at last check
kirk_billing_showReturn 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 creditkirk_billing_checkoutCreate 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 whenkirk_billing_usageReturn 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 actuakirk_bulk_howtoReturn 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_largekirk_demo_tradingRuns 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 marketkirk_demo_uavRuns 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 acoukirk_verify_engineVerify 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 HOST DEFAULT engine sha (kirk_version). That is the legacy defaultkirk_list_modelsEnumerate 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 / kirkirk_infer_legacyScore 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 refactoringkirk_score_bookScore 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 datkirk_score_l2_bookScore a sequence of full L2 order books as one chain and return per-book entropies plus engine attestation. Purpose: Score complete books — prices, sizes and order counts — rather than prices alone. This is the v2 book contract; it carries information the price-only contract cannot. STATE POLICY,kirk_score_book_batchScore 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 bookkirk_render_bookRender 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 conventionkirk_score_randomSynthesize 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
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