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685,449 tools. Updated 2026-10-21 10:46

"Samsung" matching MCP tools:

  • Heuristic chip manufacturing LEAD TIME estimator (MANUFACTURING CYCLE TIME). Given total mask layers (or a processNode to default them), foundry utilization % (optional — defaults from live foundry-allocation data), and packagingType, returns min/max bands: fabDays, fabWeeks, packagingWeeks, totalWeeks, plus effectiveDpml (days per mask layer), the operating-curve weight, a resolved-inputs echo, assumptions, methodology, and public-source citations. USE THIS for: "how long to manufacture this chip" — wafer-fab cycle time + packaging assembly/test time for hypothetical chips; cycle-time sensitivity to fab utilization or packaging class (conventional vs flip-chip vs CoWoS). DO NOT USE for: booking windows / allocation lead time — how long until a booked-out foundry STARTS wafers, publicly 52–156+ weeks at N3-class nodes and CoWoS (use get_foundry_allocation); chip cost (use calculate_chip_cost / get_accelerator_costs). Provide maskLayers (integer 10–200) or processNode (tsmc-n3 | tsmc-n5 | tsmc-n7 | tsmc-n16 | tsmc-28 | samsung-3nm | samsung-5nm | samsung-7nm | samsung-14nm | intel-7 | intel-16 | gf-12lp | gf-fdx | umc-22-28 | umc-40 | smic-28). packagingType accepts coarse classes (conventional | flip-chip | cowos, default flip-chip) or any platform packaging id (fc-bga, wirebond-bga, cowos-l, copos, ...). Utilization ≤80% settles at the best-case band; ≥95% converges to the worst-case bound (FabTime operating-curve shape). Heuristic from public DPML benchmarks — directional, confidence LOW, not a foundry quote. Cite as "Silicon Analysts — Lead Time Estimator".
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  • Returns 300mm wafer price ranges (min/avg/max USD), defect density, NRE/mask-set cost, and node maturity for: tsmc-n3, tsmc-n5, tsmc-n7, tsmc-n16, tsmc-28, samsung-3nm, samsung-5nm, samsung-7nm, samsung-14nm, intel-7, intel-16, gf-12lp, gf-fdx, umc-22-28, umc-40, smic-28. Optional `node` filter narrows to one. ALWAYS read `citation` before using a price in a cost model: it names the corroborating sources and carries the caveat that decides whether the number is usable. Some sellers report a foundry segment operating loss, so their quote is a positioning price rather than a cost-recovering one; `citation` says so explicitly, and `defectDensity`/`nreCost` are null where no public basis exists rather than being estimated. USE THIS for: looking up wafer cost for cost modeling, comparing foundries at the same node. DO NOT USE for: per-chip cost (use get_accelerator_costs or calculate_chip_cost); packaging-related cost (use get_packaging_costs). Returns INVALID_PARAMS if node is not in the valid set. Each record carries the source attribution string. Refreshes monthly.
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  • Search companies registered with DART, South Korea's corporate disclosure system, by name, 6-digit stock code, or 8-digit DART corp_code. Returns the corp_code required by the other dart_* tools. Not this tool for: US registrants (use search_edgar_company). Japan, Taiwan and Europe have no search tool — reach them through query_db on the companies table. Args: - query: company name in Korean ('삼성전자') or English ('Samsung Electronics'), 6-digit KRX stock code ('005930'), or 8-digit corp_code - listed_only: restrict to KRX-listed companies (default true). Set false to include ~90k unlisted entities. - limit: max results, 1-50 (default 10) Returns: {count, companies: [{corp_code, corp_name, corp_name_en, stock_code}]} — corp_name is the Korean name DART registers, corp_name_en the registered English name where the company files one (about three quarters of Korean issuers). stock_code is null for unlisted companies. Match priority: exact stock code > exact Korean name > listed Korean partial > unlisted Korean partial > English name. English matching reads our own company table, so it covers issuers whose English name we hold, not every DART entity. Examples: - {query: '삼성전자'} -> corp_code 00126380, stock_code 005930 - {query: '카카오', listed_only: false} -> listed 카카오 plus unlisted same-name entities - {query: 'Samsung Electronics'} -> 삼성전자 (matched on the registered English name) Use when you need a corp_code or must disambiguate similar names. Don't use for US companies (use search_edgar_company). Errors: DART_API_KEY not configured; no match returns count 0 (not an error).
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  • Get daily OHLCV price history from the local finbridge database (populated by the nightly ingest jobs). Rows are returned newest first. Listed equities and ETFs. Japan and Europe carry no prices at all, and crypto is not served. Price coverage by market — we only store what we have redistribution rights to: - Korea (DART + Financial Services Commission): full daily history, corporate-action adjusted. SERVED. - Taiwan (TWSE OpenAPI, Open Government Data License): daily history. SERVED. - US (Databento EQUS.SUMMARY): daily history from 2023-03-28. SERVED. Split-adjusted; dividend-adjusted closes exist where SEC-reported dividends do (adj_close). - Japan: NOT served. EDINET publishes disclosure documents, not prices, so we hold Japanese filings and the company master but no quotes. Args: - company: a ticker (US 'AAPL', TW/JP 4-digit '2330'), a KR 6-digit stock code ('005930'), or a company name in the local language or English ('TSMC', 'Toyota', '삼성전자'). Resolution priority: exact ticker > 6-digit KR code > exact name (name or English name) > partial name (multiple partial matches return a candidate list error). - from / to: optional YYYY-MM-DD range bounds (inclusive) - limit: max rows, 1-500 (default 60) - response_format: 'markdown' (default) or 'json' Account limits: a free account includes the most recent 130 trading sessions of each name. Results follow the current account's history entitlement. When the window is trimmed the response carries a plan_limit field saying so. Returns: {company: {name, source, ticker|stock_code}, count, truncated, prices: [{date, open, high, low, close, volume}]} — newest date first; truncated=true means older rows exist beyond 'limit'. Examples: - {company: '005930', limit: 30} -> last 30 KR trading days for Samsung Electronics - {company: '005930', from: '2026-01-01', to: '2026-06-30'} -> Samsung Electronics H1 2026 Use when: historical closes/volumes for charting or return calculations from ingested data. Don't use for crypto, which is not served. FinBridge has no real-time equity quote tool — equity prices here are end-of-day closes from the nightly ingest; the only live data is regulator filings (get_dart_filings / get_edgar_filings). Errors: unknown company -> no-match or candidate-list error; JP/EU company -> no-prices error (those markets carry statements only); no price rows -> a market-specific hint (new listing, delisted, nightly lag).
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  • Get the latest valuation snapshot for one KR, US, or Taiwan company from the local finbridge database: market cap (latest close x shares) with PER, PBR, PSR, ROE, debt ratio, and 3-year revenue/net-income CAGR, joined to the company's latest annual fundamentals. Includes metric-level calculation basis, dates, sources, missing reasons, and 1-2 same-market percentile hints. Computed by the nightly valuation ingest job. Share counts: KR uses data.go.kr listed shares, US prefers SEC-reported shares, and Taiwan uses exchange-reported shares; the nightly job can fall back to net_income / eps_diluted when a positive result is available. PER prefers price / eps_diluted, falling back to market_cap / net_income. Taiwan exchange-published PER/PBR replace derived values when present. Any derived ratio whose required denominator is null or <= 0 is returned as null. Args: - company: US ticker (e.g. 'AAPL'), KR 6-digit stock code (e.g. '005930'), or company name. Resolution priority: exact ticker > 6-digit code > exact name > partial name (multiple partial matches return a candidate-list error). - per_multiples: optional 1-5 positive user-supplied PER assumptions (maximum 1000) - pbr_multiples: optional 1-5 positive user-supplied PBR assumptions (maximum 100) - response_format: 'markdown' (default) or 'json' Returns the existing valuation fields plus metric_evidence and multiple_scenarios. Ratios are plain numbers; roe/debt_ratio/CAGR and scenario upside/downside are in percent. A scenario is arithmetic from the user's multiple, not a target-price recommendation. If no multiple is supplied, no multiple or target price is invented. Examples: - {company: '005930'} -> Samsung Electronics PER/PBR/ROE plus "PER in the cheapest N% of the KR market" - {company: 'AAPL'} -> Apple valuation snapshot with US-market percentiles Caveats: if statements are in another currency than the listing (Korean listings reporting in USD/CNY/JPY), statement values are converted at one Federal Reserve H.10 rate on or before the price date before PER/PBR/PSR (fx_conversion shows the rate and date; no rate → null). ROE/debt ratio need no conversion; growth across a statement-currency change is null. market_cap keeps the listing currency. KR fundamentals are K-IFRS and US are US-GAAP, so cross-market comparisons are approximate. This is snapshot data (not real-time) and not investment advice. Use when: assessing one company's valuation/quality at a glance, or comparing it to its own market. Don't use for many-company ranking (use query_db) or raw statements (get_dart_financials / get_edgar_financials). Errors: unknown company -> no-match or candidate-list error; 'no valuation snapshot' -> the valuation ingest job has not produced a row for this company (needs a price and latest-annual fundamentals).
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  • Foundry IR ECONOMICS — per-foundry, per-process-node, per-fiscal-quarter wafer ASP (min/max/blended, USD per 300mm-equivalent wafer, $250-grained) and fab UTILIZATION (%), derived exclusively from PUBLIC IR materials (earnings releases/transcripts/decks, trade press) via a documented scaling calculation (rev-mix-v1): reported revenue × reported node revenue-shares × reported wafer shipments, allocated on pinned analyst prior ratios. Covers tsmc | umc | intel | samsung | smic | gf. Every row carries source_urls + release_dates + confidence (high/medium/low); utilization is 'stated' (company said it — UMC/SMIC style) or 'derived' (shipments vs capacity estimate, capped medium) and NEVER fabricated per node. include_facts=true returns the underlying evidence facts (verbatim quote + source per datum). Also returns node_margin_estimates for TSMC: per-node est. wafer price / est. wafer cost / est. GROSS MARGIN % with ranges (N3/N5/N7/N16/N28+/N2) — single-vintage Silicon Analysts ESTIMATES from public analysis, explicitly labelled (TSMC does not disclose per-node margin; company-level GM is quarterly IR). USE THIS for: "what does a TSMC 3nm wafer sell for and how has it moved by quarter?", "TSMC blended ASP trend", "UMC utilization last quarter", "N3 share of TSMC revenue over time", "estimated gross margin by node", node-economics history for models. DO NOT USE for: the current spot wafer price band only (use get_wafer_pricing — that is the live analyst-consensus band this dataset cross-validates against); allocation/lead-time/booking (use get_foundry_allocation); chip-level cost (use calculate_chip_cost / get_accelerator_costs). Filters: foundry, node (canonical token, e.g. n3 | 22-28nm | 18a), node_group (leading_3nm | class_5nm | ...), quarter (2026Q1 | 2025FY), from/to range, include_facts, limit. LATEST period per foundry is free; multi-period HISTORY (quarter/from/to) requires a Pro key — free callers are clamped to latest with an explanatory meta.note (never an error). Sparse-disclosure foundries (Intel, Samsung) return nulls/low confidence rather than invented numbers. Refreshes weekly (Mon 14:30 UTC) + each earnings season. Cite as "Silicon Analysts — Foundry IR Economics".
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Matching MCP Servers

  • Comparison references for one company across KR / US / TW / JP / EU. The default uses a sourced business theme or broad source classification and does not assert direct competition or add unrelated companies to fill the limit. Explicit rank='size' returns same-currency size references and does not assert an industry relationship. Also returns the company's business-segment revenue split where available (Japan from 有価証券報告書 XBRL, the US from SEC DERA financial-statement datasets; US segment names are usually end markets, not industries) — informational unless rank='segments'. Args: - company: US ticker ('AAPL'), KR 6-digit code ('005930'), TW/JP 4-digit code ('2330', '7203'), or a company name (local or English). - market: 'kr'|'us'|'tw'|'jp'|'eu' (optional) — disambiguates codes/names shared across markets (TW and JP both use 4-digit codes; 'eu' companies are addressed by ISIN). - limit: 1-10 peers (default 5). - same_market_only: true = restrict peers to the company's own market (default false — a KR chipmaker can sit next to a US one). - rank omitted = business-related references; 'size' = explicit size references with verified equal market-cap currency; 'segments' = rank by business-mix similarity — each company's segment revenue shares are mapped to standard industries (companies without segment data count as 100% their own industry) and compared by cosine similarity, ties broken by normalized size. Conglomerates (Sony: games/music/pictures/electronics/finance) then get conglomerate peers instead of whichever single bucket they were filed under. - response_format: 'markdown' (default) or 'json'. Returns: existing fields plus policy_version, purpose, insufficiency_reason; each peer also has selection_reason, comparison_role and evidence_status. Broad/theme rows are business-related references, not verified direct competitors. Explicit size rows are size-reference only. Examples: - {company:'7203'} -> Toyota + transportation-equipment peers, with its Automotive / Financial Services segment split - {company:'005930', same_market_only:true} -> Samsung Electronics + KR tech-hardware peers only - {company:'6758', rank:'segments'} -> Sony ranked against other multi-segment conglomerates by business mix Use when: building a comparison table or choosing competitors for a financial comparison. Don't use for strategy screens (screen_*) or for full financial statements (get_dart_financials / get_edgar_financials). Notes: curated business themes remain separate from official company-level classifications. Segment names may be geographic (Japan/Asia/USA) when a company defines its reportable segments by region. Unverified cross-currency absolute market-cap ordering is never used. Errors: unknown/ambiguous company -> candidate list; no classification -> basis_kind='size' with a note.
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  • AI Hardware Bottleneck Board — eight points where AI accelerator supply can stall (CoWoS-L packaging, HBM, TSMC N3, the HBM base die on foundry logic, large ABF substrates, T-glass, test equipment, InP lasers), each with a judged state: loose / balanced / tight / allocated / sold_out, or watch. Every node returns the evidence behind its state (with the company's own words where they exist), five standard numbers — lead time, price change, share under contract, customer deposits, capacity and timing — each with an evidence grade and source links, what would change the state, and the next dated checkpoint. Also returns the customer-deposit table (TSMC, Samsung, Micron, SK hynix balance-sheet lines) and claims that failed against primary sources. Grades: A = a filing or the company's own words; B = two or more independent outlets; C = one outlet; D = echo. A state moves only on A or B evidence; judgments are weekly, dated, and never overwritten. USE THIS for: "is CoWoS / HBM / ABF substrate supply constrained right now, and on what evidence?", "which AI hardware inputs are sold out or allocated?", "who is prepaying for capacity?", checking whether a widely repeated shortage claim (e.g. "CoWoS sold out through 2026") is in the company's own words, finding the next event that could change a bottleneck. DO NOT USE for: per-node lead-time or customer-share time series (use get_foundry_allocation); fab-level capacity (use get_fab_capacity); HBM prices and vendor share (use get_hbm_market_data). Filters: node (id or name fragment: cowos-l, hbm, n3, hbm-base-die, abf-substrate, t-glass, ate, inp-laser), state, include_history (bool — every earlier judgment with its date, rules version and reason). Missing numbers are null, never estimated. Fully public at full fidelity for every tier including anonymous. Cite as "Silicon Analysts — AI Hardware Bottleneck Board".
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  • Returns 10 HBM market sub-tables: accelerators, specs, marketShare, spotPrices (RETIRED 2026-07-28 — frozen), leadingIndicators, qualificationFeed, revenueForecast, supplierRevenue, validationChecks, bitDemand. Optional `table` parameter narrows to a single sub-table; omitting returns all 10. USE THIS for: HBM3/3e/4 generation specs, SK Hynix/Samsung/Micron share of HBM revenue (marketShare: Q2 2026, Counterpoint Research, the latest quarter; the quarterly series and IDC full-year actuals are get_market_dataset dataset='hbm-market-share'; not share of bit shipments), derived HBM bit demand by SKU class and customer type (bitDemand, EB ranges, monthly). spotPrices is a RETIRED series: no public HBM spot market exists in any generation — HBM sells via annual/multi-year LTAs. Its rows are frozen estimates served for the record with per-row retired marking; for current, sourced HBM pricing use get_market_dataset with dataset='hbm-pricing'. bitDemand is NOT a workload split — it is a SKU-class/customer-type cut. Dominant HBM SKUs are dual-use, so a training-vs-inference HBM attribution would be dishonest; no public source publishes one. DO NOT USE for: HBM price history or current HBM pricing (use get_market_dataset dataset='hbm-pricing'); per-accelerator HBM cost in a specific chip (use get_accelerator_costs.costBreakdown.hbmCostUsd); HBM cost in a hypothetical chip cost calc (use calculate_chip_cost with hbmStacks/hbmCost). Returns INTERNAL_ERROR if the upstream Supabase HBM tables are unreachable. Only two sub-tables refresh on a schedule: qualificationFeed (Mon/Thu) and bitDemand (monthly, 1st). accelerators, specs and validationChecks are hand-curated reference tables, the editorial tables are revised by hand, and spotPrices is frozen (retired 2026-07-28). meta.table_freshness dates each sub-table; meta.data_freshness.stale flags an overdue refresh.
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  • Sourced HBM qualification tracker: which memory vendor (SK Hynix, Samsung, Micron) passed which AI-accelerator customer's qualification (NVIDIA Vera Rubin/GB300/B300/H200, AMD MI350/MI325X, Broadcom), by generation (HBM3/HBM3E/HBM4) and stack height. Returns `matrix` (current status per vendor×customer×generation, each row dated + source URL + confidence) and `timelines` (per-relationship status-change history back to 2022, e.g. sampling → in_qualification → qualified → volume_shipping). Refreshed Mon/Thu 09:00 UTC; a status change auto-publishes once corroborated (a primary source, or 2+ independent sources that agree) and is not human-reviewed before publication. meta.data_freshness.stale reports whether the refresh is current; superseded timeline events carry superseded: true and the published correction. USE THIS for: "who supplies HBM4 for Vera Rubin?", "did Samsung pass NVIDIA qualification?", "Micron HBM4 status", qualification timeline/history questions, HBM supply-eligibility analysis. DO NOT USE for: HBM pricing/market share (use get_hbm_market_data); per-chip HBM cost (use get_accelerator_costs). Filters: vendor (enum), customer (substring), generation (enum), include_timelines (boolean). Anonymous callers may receive timelines truncated to the latest event per relationship — full history with a free API key (https://siliconanalysts.com/developers). Cite as "Silicon Analysts — HBM Qualification Tracker".
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  • Foundry & advanced-packaging ALLOCATION — the current-state snapshot per node/tech (TSMC/Samsung/Intel/... × N2/N3/CoWoS-L/SoIC/...) plus optional time-series HISTORY. Current fields: allocation_status (fully_booked → available), lead_time_weeks_min/max + trend, utilization, price_trend, geo_risk, customers, capacity_current/target, customer_shares, allocation_note. With include_history=true, returns the tracked series from capacity_signals: lead_time / booking-window, pct_locked (%-capacity-locked), customer_allocation (publicly-reported per-customer share), cowos_capacity, foundry_utilization — each point dated (as_of) with provenance. No competitor publishes allocation as a structured, queryable feed. USE THIS for: "who has CoWoS allocation and how much?", "what's the booking lead time for N2?", "how locked is 2026 CoWoS capacity?", allocation/lead-time trend over time. DO NOT USE for: per-chip cost (use get_accelerator_costs / calculate_chip_cost); HBM market share/pricing (use get_hbm_market_data); HBM qual status (use get_hbm_qualification). Filters: foundry, node, category, customer, history_metric, include_history (bool), limit. Sourced public estimates (analyst/press/earnings), human-reviewed; every record carries provenance.confidence_tier. wafer_price is intentionally omitted. Cite as "Silicon Analysts — Foundry Allocation".
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  • Fab Capacity — per-fab, per-tech-node-class capacity from the fabs + fab_capacity_snapshots time-series (100+ fab and advanced-packaging sites: TSMC, Samsung, Intel, SMIC, GlobalFoundries, SK hynix, Micron and more; Frontend in kwspm, Backend advanced-packaging in k units/month). Default mode returns the LATEST state per (fab, node class) at/before as_of, joined with fab metadata (name, foundry, country, status) and availability_status (fully_booked → available). series=true returns the full dated series — node conversions appear as capacity shifting between node-class rows across effective_dates (e.g. 28nm shrinking while 7nm grows). Every reading carries sourcing metadata (foundry_ir / wfe_vendor_earnings / government_filing taxonomy + citation + confidence) and is_projection for forward-looking guidance. Latest state: all tiers (incl. anonymous). series=true: free key → preview, Pro/Enterprise → full series. USE THIS for: "what is TSMC's 3nm-class installed capacity by fab?", "which fabs are fully booked?", "how is Fab 14's mature-node capacity being converted over time?", country-level capacity aggregation. DO NOT USE for: node-level annual wafer starts (use get_wafer_pricing's foundry context or /api/v1/foundry endpoints — different granularity, deliberately separate); allocation/lead-time status per node (use get_foundry_allocation). Filters: fab_id, foundry, country, tech_node_class, as_of (latest-state cutoff), series (bool), limit (max entries returned: fab·class rows in latest state, newest readings with series=true). Access: latest state is free for all tiers (incl. anonymous); series=true returns a preview on a free key and the full series for Pro/Enterprise (anonymous gets an empty series + a get-a-key note). Cite as "Silicon Analysts — Fab Capacity".
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  • List major-event disclosures (주요사항보고서, DART type B): capital increases, mergers, convertible bonds, treasury stock, bankruptcy, lawsuits, etc. Optionally filter report names with a regex. Not this tool for: the full disclosure list or other report categories (get_dart_filings — periodic reports, securities issuance, ownership, KRX notices), US 8-K events (get_edgar_filings), or the cross-market stored feed (get_disclosure_feed). What this adds over get_dart_filings type='B': a 'kinds' regex over Korean report names (e.g. '증자|합병|전환사채'), a 180-day default window tuned for event scans, and matched-count totals — so use it when the question is 'which companies announced X', not 'what did company Y file'. Args: - corp: optional — Company: Korean name (e.g. '삼성전자'), 6-digit stock code (e.g. '005930'), or 8-digit DART corp_code (e.g. '00126380'). Omit for market-wide events. - from / to: YYYY-MM-DD (default: last 180 days) - kinds: optional JavaScript regex matched against the Korean report name, e.g. '증자|합병|전환사채' (capital increase | merger | CB) or '자기주식' (treasury stock). Filtering runs over every event in range when FinBridge's index covers the window, otherwise over the most recent 100 events DART returns. - limit: max results, 1-100 (default 20) Returns: {total, page, filings: [{rcept_no, corp_name, report_nm, flr_nm, rcept_dt, url}]} — same shape as get_dart_filings. When kinds is given, total = matched count within the scanned window. Examples: - {corp: '삼성전자', kinds: '자기주식'} -> Samsung treasury-stock decisions in the last 180 days - {kinds: '유상증자', from: '2026-01-01', to: '2026-06-30'} -> market-wide rights offerings in H1 2026 Use when: event-driven screening (rights offerings, mergers, CBs, treasury stock, lawsuits) market-wide or for one company. For every filing category, or when you already know the report you want, use get_dart_filings. Errors: no events in range (DART status 013) -> widen dates; invalid kinds regex; unknown company -> search_dart_company.
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  • Run a single read-only SELECT query against the local finbridge database (ingested KR/US fundamentals, filings, daily prices). The statement must start with SELECT or WITH; multiple statements, PRAGMA, and any write/DDL keywords (INSERT/UPDATE/DELETE/DROP/ALTER/CREATE/ATTACH/...) are rejected. The query runs in a separate read-only process with SQLite authorization, a 2-second deadline, two concurrent queries per server process, and a 1 MB result budget. Free accounts cannot query raw history or history views; the latest-annual snapshot remains available. The escape hatch for questions no dedicated tool answers — Japan, Taiwan and Europe are largely reachable only this way. Prefer get_valuation or get_peers for ordinary single-company work (they handles per-market period and currency rules that a hand-written query will get wrong), and call get_db_schema first for the table shapes. Args: - sql: one SELECT (or WITH ... SELECT) statement. A single trailing ';' is tolerated. - limit: max rows returned, 1-500 (default 50) - response_format: 'markdown' (default, table) or 'json' (compact) Returns: {columns: [name], rows: [[cell, ...]], row_count, truncated} — truncated=true means more rows matched than 'limit'. Examples (v_financials / v_latest_annual views are the easiest entry points): - Largest companies by latest annual revenue: "SELECT name, ticker, stock_code, fiscal_year, revenue FROM v_latest_annual ORDER BY revenue DESC LIMIT 10" - Samsung Electronics annual trend: "SELECT fiscal_year, revenue, operating_income, net_income FROM v_financials WHERE stock_code = '005930' AND quarter = 0 ORDER BY fiscal_year DESC" - KR vs US company counts: "SELECT source, COUNT(*) AS n FROM companies GROUP BY source" - Recent Samsung Electronics closes: "SELECT date, close FROM prices_daily p JOIN companies c ON c.id = p.company_id WHERE c.stock_code = '005930' ORDER BY date DESC LIMIT 20" (prices_daily holds KR, US, TW; US history starts 2023-03-28) Use when: custom aggregation/joins over ingested data that no dedicated tool expresses. Don't use for anything that writes — it will be rejected. FinBridge has no real-time equity quote tool — equity prices here are end-of-day closes from the nightly ingest; the only live data is regulator filings (get_dart_filings / get_edgar_filings). Errors: non-SELECT input, ';' inside, or forbidden keywords -> rejected with the reason; unknown table/column -> SQL error with a hint to call get_db_schema first.
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  • Search SEC filings (10-K, 10-Q, 8-K, registration statements/prospectuses and press exhibits; S&P 500 coverage, ~10 years) with hybrid semantic + keyword retrieval. TWO MODES. Search mode (pass `query`): results ranked by relevance, highest first. FETCH MODE (omit `query`): no ranking at all — pass an issuer plus any of form_type / fiscal_year / accession_number / section and get that filing's sections back in filing-date-desc then document order, in tens of milliseconds. Use fetch when you already know WHICH document you want and only need its text. ALWAYS pass `issuer` (ticker, cik or company_name) — the company the question is about — plus `fiscal_year` and/or `form_type` when you know them. Scoped calls are fast and precise. A call with no issuer runs as scope=cross_company: slower, ranked by relevance only, and the response sets `quality_caveat` — check for that field. Use scope=cross_company deliberately only for questions that are genuinely about many companies ("which filers name NVIDIA as a supplier"). Built for agents: every hit is a ready-to-cite payload — exact filing-section text, form type, filing date, accession-numbered citation, source URL and a 0-1 confidence score — no HTML parsing, no EDGAR pagination. Use for revenue/segment figures, risk factors, M&A and contract terms, customer/supplier concentration, and any claim that must trace to a primary source. Fetch mode pages: pass the response's `next_offset` as `offset` to read past `limit`. Returned windows overlap; counts of a term over returned text are not document counts. `partial: true` means retrieval degraded; an empty result is then not proof of absence. Coverage is NOT US-only: Sweden/Bolagsverket, Japan/EDINET, Korea/DART annual reports are included. Those issuers have no US ticker — pass `issuer.company_name` (e.g. "Sivers Semiconductors", "Samsung Electronics", "Ajinomoto") or scope a whole market with `jurisdiction` (["SE"], ["JP"], ["KR"]).
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  • Type text into the focused field on Android. CRITICAL: call this AFTER device_tap / device_tap_by_text completes — do NOT issue the focusing tap and this type in parallel, or the type will race the focus change and land in the previously-focused field (observed on a banking-app login: username+password concatenated into username box). method="keys" (default): decompose ASCII to keycode events (DOWN/UP with shift) — most reliable; non-ASCII chars (CJK/emoji) auto-fall-back to IME injection for that segment. method="ime": IME injection only — full UTF-8 in one shot, but Samsung IMEs intercept `.`/`@`/`_` as autocomplete/action shortcuts and may trigger system gestures. method="shell": shell `input text` — slowest, and Samsung IME drops `@`/`.`/`_`. Optional clearFirst wipes the field first; pressKey sends a keycode after typing. All three methods inject — there is no kernel input path for text, and no tool that types a whole string as one. To get text in as real kernel input you compose the reports yourself with device_uhid_create plus device_uhid_input (or device_uhid_key_press per character); only worth it when the app filters injected text.
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  • HOW TO CALL THIS TOOL — read before every call: Decompose the user's request into filters first. Only what's left over goes in query. STEP 1: brand name → brand filter. STEP 2: product category → category filter. STEP 3: price → min_price/max_price. STEP 4: RAM, storage, screen size, resolution, refresh rate, wattage, Wi-Fi generation → constraints. STEP 5: what remains → query. BAD: query='Sony headphones under £200' | GOOD: brand='Sony', category='Headphones', max_price=200, no query. BAD: query='tablet' | GOOD: category='Tablets', no query. BAD: query='macbook neo' | GOOD: brand='Apple', category='Laptops', query='neo'. BAD: query='Samsung QLED TV' | GOOD: brand='Samsung', category='TVs', query='qled'. If brand+category alone cover what the user wants, omit query entirely. Only put differentiating terms in query: model lines (neo, ultra, oled), variants, model numbers (WH-1000XM5, s25 ultra). Query words must appear in the title, except words naming the category ('router' in Networking) and bare numbers or specs ('4070', '16GB'), which are ignored when finding products and only rank them. Put a model number with its prefix ('RTX 4070', not '4070') and check each title for it. Leave out use-case words like gaming, cheap or best. CROSS-CATEGORY NOTE: Gaming headsets → category='Headphones', query='gaming headset'. The Gaming category is consoles/controllers/accessories only. Always set lite=true (it still carries `attributes`). If 0 results, broaden the query or drop filters (but never present a near miss as meeting a requirement). Searches 26,000+ UK electronics products across 7 retailers with price comparison. Prices are in GBP. Every listing is new (refurbished and used are excluded). PRICE COMPARISON: for a final pick with offer_count > 1, get_product returns offers[] (sorted in-stock first, then cheapest): show the cheapest in-stock retailer, the other prices with the difference and the exact saving among in-stock offers. Before claiming a saving, read offers[].title (from get_product): they must name the same model; if they differ, don't claim one. Before recommending any pick, check its title is the product type asked for (not a cable, accessory or adapter). COMPARING SPECS: compare products from the `attributes` in the search results, not by calling get_product on each. Every spec known for a product is there as {status, value}, or {status, values} when conflicting, without sources; names and units are as in `constraints`. 'confirmed' (two or more retailers state the same value) and 'inferred' (one retailer's title states it) are both the product's spec: state the value. Only `conflicting` (retailers disagree: say so, don't pick one) or a missing name (unknown) needs a caveat. A product with no `attributes` has none of these seven specs known: say so only if the user asked about one. Call get_product only for your final 1-3 picks, and only when you need what search lacks: what only the retailer's description has (processor, GPU, ports, weight, battery), or every retailer's offer and buy link (search results carry only the best offer's purchase_url (cheapest in stock)). A pick with offer_count 1 needs no call unless the user asked for a description-only detail. Don't guess those details from titles. SPEC REQUIREMENTS: put exact requirements in `constraints`, not in query, and always set `category` (and brand if known) with `constraints`: a search of only specs is rejected. If a requirement is ambiguous (e.g. '16GB' could be RAM or storage), ask the user or search without that constraint. With constraints, every product has `constraint_status` per name: 'matched' = a retailer's title states a value that meets it. 'unverified' = not known to meet it: check `attributes[name]`, where `conflicting` means retailers disagree and missing means unknown. Never treat 'unverified' as a match or say a product meets a requirement because it was returned: tell the user it is unconfirmed. Products whose stated value fails are left out (`excluded_by_constraints`). Matched results come first, also with sort='price_asc'. With constraints, `total` counts the products that match every constraint and `unverified_total` the unverified products that passed the other filters (only some may be in `products`). If `total` is 0, say no product is known to meet every requirement and offer the unverified ones only as unconfirmed. If `candidates_truncated` is true, the first 2,000 candidates in the chosen sort order were checked and more exist: add a brand or category, or a narrower query, and search again before saying nothing matches. If the search was already narrowed, tell the user the results may be incomplete. STOCK: availability is in_stock, low_stock, out_of_stock or unknown (the retailer gave no stock signal: say so, don't assume). When availability is out_of_stock, mention it as an alternative and suggest checking back — do not silently omit it. purchase_url is a trustrails.app/go/ redirect through an affiliate link; TrustRails may earn a commission, and the price is the same. Colour variants have separate barcodes and are separate products: when price matters, search again without the colour or check other colours of the same model.
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  • Retrieve detailed narrative information about the eSIM Finder product and connector, beyond what the search/checkout tools surface. Use this for any question that is NOT a price/plan search: how the product works, device compatibility and how to install, the Annual Travel Pass, the country coverage of a regional bundle, plan tiers, and — importantly — help when something is not working or after the user has bought (troubleshooting, error messages, managing an installed eSIM). Reach for it on any "how do I...", "what is...", "my eSIM is not working", or "what do I do after buying" question. Pass one of the following `topic` values: `about` (what the eSIM Finder connector is and its scope, plus that eSIM Finder is also a free iOS/Android app with a website FAQ and blog), `faq` (18 common Q&A pairs from esimfinder.io/faq — quick reference for first-time users), `travel-pass` (full Annual Travel Pass guide including the complete 130-destination coverage list — best when the user is weighing whether Travel Pass fits their travel pattern), `compatibility` (which phones support eSIM and how to check, per-device install steps for iPhone / Samsung / Pixel / other Android, the pre-travel checklist, and full troubleshooting — no signal or no data after install, activation and QR-code errors, specific iOS/Android error messages such as "This Code is No Longer Valid" or "Cellular Plans From This Carrier Cannot Be Added", slow data, carrier-lock, and network reset; use this whenever the user cannot get the eSIM to install or connect), `regions` (live country lists for every regional eSIM bundle currently on sale — Global, Europe, Europe Lite, Balkans, CIS, Asia, Oceania, Middle East, MENA, Africa, CENAM, Latin America, Caribbean, North America — generated from the current catalog; use this when the user asks "what countries are in X bundle?" or "how does Europe differ from Europe Lite?"), `product-overview` (what eSIM Finder is, app download links for iOS/Android, key features, support contacts, and managing an installed eSIM: safely removing or transferring it, a lost or stolen phone, finding the ICCID, hotspot/tethering, Wi-Fi calling on the primary number, and what to do when data runs low), or `plan-tiers` (compare Fixed vs Unlimited Essential vs Premium Unlimited data tiers). The response is markdown text from the eSIM Finder knowledge base; the regions topic is generated live from the current catalog. Prefer this tool over guessing — the knowledge base is the canonical source.
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  • NightWatch Knowledge Graph lookup for a COMPANY/entity (equities & RWA universe: Samsung 'samsung-electronics', SK Hynix 'sk-hynix', 'tsmc', 'nvidia', 'asml', 'arm', ...). Returns SOURCED data only — every row carries a citation URL (the KG refuses uncited data): (1) numeric fundamentals (revenue, net income, market cap, business segments, dividend, market-share rankings), (2) typed relations (supplies / competes / customer_of / licenses — e.g. Samsung supplies NVIDIA HBM, competes with TSMC in foundry), and (3) a live HyperLiquid price block when the entity is tradable. Use this BEFORE reasoning about a company's fundamentals, competitors, supply chain, or a hedge on its equity perp. Input accepts a slug or a plain company name (fuzzy-matched).
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  • KRW Macro Stress Score (0-100) — combined 5-component signal blending US 3Y treasury (FRED), VIX, foreign ownership proxy on SK Hynix + Samsung (mcap-weighted foreign %), USD/KRW momentum, and Korean semiconductor equity. Rolling 120d percentile over a 2-year backfill. Returns score, regime (calm/neutral/caution/risk_off/crisis), direction (krw_weakening/stable/strengthening), per-component breakdown with raw values and freshness, plus an AI-generated factual note (no trading advice). 15-min cache. Positioning: KRW macro stress filter for trading bots (not a kimchi-premium predictor — V0 validation showed corr=-0.049 with kimchi premium). 💰 Price: $0.05 USDC per call 💳 Payment: x402 micropayment on Base, Polygon, or Solana 🔧 Client: AgentCash, Pay.sh, or any x402 SDK 📖 Docs: https://api.printmoneylab.com/.well-known/x402 Returns: score, regime, direction, components{us_rate_stress, risk_sentiment, foreign_flow, fx_momentum, semiconductor} each with score+raw+freshness, ai_note, market_hours{krx, us}, as_of, method, degraded[].
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  • List corporate disclosure filings from DART, optionally filtered by company, date range, and disclosure type. Report names are in Korean. Not this tool for: US filings (get_edgar_filings), a cross-market feed already stored here (get_disclosure_feed), or major-event reports specifically (get_dart_major_events, a narrower slice of this one). Args: - corp: optional — Company: Korean name (e.g. '삼성전자'), 6-digit stock code (e.g. '005930'), or 8-digit DART corp_code (e.g. '00126380'). Omit for a market-wide list. - from / to: YYYY-MM-DD (default: last 90 days) - type: DART pblntf_ty — A=periodic reports(정기공시), B=major events(주요사항보고), C=securities issuance(발행공시), D=ownership/stake(지분공시), E=other(기타공시), F=external audit(외부감사관련), G=funds(펀드공시), H=asset securitization(자산유동화), I=KRX disclosures(거래소공시), J=fair trade(공정위공시) - limit: results per page, 1-100 (default 20); page: page number (default 1) Returns: {total, page, filings: [{rcept_no, corp_name, report_nm, flr_nm, rcept_dt, url}]} — url opens the filing in the DART viewer. Pass rcept_no to get_dart_document to explore its primary body by outline, section, or table. Examples: - {corp: '삼성전자'} -> Samsung filings in the last 90 days - {type: 'A', from: '2026-03-01', to: '2026-03-31'} -> March periodic reports market-wide Use to track what a company disclosed. For major events with keyword filtering use get_dart_major_events. Errors: no filings in range (DART status 013) -> widen dates or drop filters; unknown company -> search_dart_company.
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