mcp

Reviewed Jan 1, 2000.

• tools: 8 tools scanned
• metadata: scanned
• packages: 1 checked

No findings.

Tools (8)

• get_fear_greed

  Get the latest Fear and Greed index value. Sourced from the CNN Fear and Greed model, cached and refreshed periodically. Values range 0 (Extreme Fear) to 100 (Extreme Greed). Returns a dict with value (0-100), label (e.g. "fear"), and timestamp, plus `current` ({score, rating, updated_at}), `history`, and the per-component `sub_indicator_scores`.

• get_earnings_calendar

  Get the earnings calendar (next + last report) for one S&P 500 ticker. Earnings are a scheduled event. This tool surfaces the next-upcoming and last-reported earnings dates and the days until the next one. When no data is available (cold cache + no live source), `available` is false and `next`/`last` are null; treat that as "unknown", not "no earnings". Args: ticker: Stock ticker symbol (e.g. "AAPL", "MSFT", "NVDA"). Case-insensitive. Returns a dict with available, next, last, days_until_next, as_of and disclaimer embedded in the payload.

• get_insider_pulse

  Get SEC Form 4 insider-trading activity — per-ticker detail or S&P 500 screener. Surfaces already-ingested Form 4 filings (the same Form 4 feed behind the market model's `form4` stage) pre-chewed into analytical context so you don't have to parse raw XBRL yourself: buyer role (officer / director / 10% owner), transaction size vs that SAME insider's own historical buy pattern (`size_vs_own_median`, `is_unusually_large` when >=2x their own median), and cluster-buy detection (`is_cluster` — 3+ distinct insiders buying the same ticker within a 10-day window, historically the stronger signal vs a single insider's trade). Every transaction links to its source SEC filing via `accession_url` — verify anything before acting. Two modes: - ticker set: per-ticker view — up to 40 most-recent Form 4 transactions over the trailing year plus `cluster_buy_active`. - ticker omitted: S&P 500 (top-100) screener — tickers with a cluster

• get_filings_digest

  Get SEC 8-K event digest — per-ticker detail or a site-wide recent feed. New EDGAR ingestion (unlike get_insider_pulse's Form 4 data, which was already ingested): polls 8-K filings and pre-chews each one so you don't have to parse raw filing HTML yourself. Event type comes from the filing's OWN structured SEC Item number(s) — GROUND TRUTH, never LLM-guessed (e.g. Item 5.02 = exec departure/appointment, Item 2.02 = earnings results, Item 2.01 = M&A completion, Item 4.02 = restatement). The `summary` field is a one-line AI narration grounded in the actual filed document text (`summary_source: "llm"`), or a factual sentence built purely from the Item label(s) when no document excerpt was available (`summary_source: "item_labels"`) — never fabricated content either way. Every filing links to its source SEC filing via `accession_url` — verify anything before acting. Two modes: - ticker set: per-ticker view — up to 15 most-recent 8-

• get_filing_language_diff

  Get the "Lazy Prices" 10-K/10-Q language diff for one ticker. Compares the two most recent 10-K (year-over-year, default) or 10-Q (quarter-over-quarter) filings' Risk Factors (Item 1A) and MD&A (Item 7 for 10-K, Item 2 for 10-Q) sections, pre-chewed so you don't have to parse raw filing HTML yourself: a real TF-IDF cosine similarity score between the two extracted section texts, plus the top added/removed sentences from a real sentence-level diff, plus a one-line AI summary grounded strictly in those diffed sentences (`summary_source: "llm"`), or a factual sentence built purely from the computed similarity/counts when no LLM is available (`summary_source: "computed"`) — never fabricated either way. Every result links to BOTH source filings via `filings[].accession_url` — verify anything before acting. Cites a known academic finding: Cohen, Malloy & Nguyen (2020), "Lazy Prices", Journal of Finance — YoY changes in 10-K Risk Factors/M

• get_institutional_activity

  Get 13F whale summaries + SC 13D/G activist alerts for one ticker. Final slice of the SEC EDGAR AI-digest layer. Two surfaces in one payload: `whale_summary` — QoQ (quarter-over-quarter) change in institutional ownership across a curated ~50-filer 13F universe (activist funds, quant shops, mega index managers, tiger cubs, sovereign wealth, etc.): new positions opened, positions closed, and the largest increases/decreases by dollar value between the two most recent 13F quarters on file. Pure computed deltas — no LLM narration, just real numbers. Institutional filer names come from SEC's own submissions data (ground truth), and every filer row links to its source 13F accession via `accession_url`. When there's genuinely nothing to compute (ticker not held by any tracked filer, or fewer than 2 quarters on file), the `narration` field says so plainly instead of a fabricated result. A filer only ever appears in `closed_positions` whe

• list_capabilities

  List all available Quantustik MCP tools and resources. Use this as the entry point when a user asks what can you do with Quantustik, or to discover the full surface area of the server. Returns a structured description of every tool and resource.

• get_started

  Onboard to the Quantustik API/MCP: anonymous access and quotas. No API key is needed — every tool is callable right now under an anonymous per-IP hourly cap. Returns the live keyless/free-key request quotas (pulled live from server config) plus the optional key-issuance URL and auth header format. Pure informational — no auth required to call it.