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MetricDuck — Financial Analysis MCP Server

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MetricDuck — Financial Analysis is answering right now. Last checked 2 min ago. It exposes 22 tools.

SEC filing intelligence for AI agents. Financials, screening, peer comparison for 5,000+ companies.

Uptime history 51 days of history · worst day 93%
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22
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What changed 40

Every tool that appeared, vanished or quietly changed what it asks for. Recorded since 9 August 2026. No other catalogue keeps this.

21 Sep a tool changed version
20 Sep a tool changed version
19 Sep a tool changed version
18 Sep a tool changed version2 times that day
18 Sep a tool changed the parameters it asks for get_filing_section
16 Sep a tool changed version
10 Sep a tool changed version3 times that day
8 Sep a tool changed version2 times that day
8 Sep a tool description was rewritten list_recent_filings
8 Sep a tool changed the parameters it asks for list_recent_filings
and 30 more, back to 9 August 2026

MetricDuck — Financial Analysis does not always answer

Over the last week it answered 98.1% of our checks. We check every 15 minutes, so you hear about the next outage within the hour — not from your users.

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Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 2 min ago.

run in your terminal
claude mcp add financial-analysis --transport http https://mcp.metricduck.com/mcp
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "financial-analysis": {
      "url": "https://mcp.metricduck.com/mcp"
    }
  }
}
~/.codex/config.toml
[mcp_servers.financial-analysis]
url = "https://mcp.metricduck.com/mcp"
.cursor/mcp.json
{
  "mcpServers": {
    "financial-analysis": {
      "url": "https://mcp.metricduck.com/mcp"
    }
  }
}
.vscode/mcp.json
{
  "mcpServers": {
    "financial-analysis": {
      "url": "https://mcp.metricduck.com/mcp"
    }
  }
}

Available tools 22

Read directly from the server with tools/list, grouped by what they act on. If a tool disappears, we record the date.

company
get_company_events
Retrieve a company's IR event CALENDAR — UPCOMING and PAST investor-relations events (earnings calls, annual/shareholder meetings, broker conferences, investor days) with the materials attached to each (deck, webcast, press release, transcript). Reach for this to answer time/calendar questions the document catalog can't: - "When does {ticker} next report / hold its earnings call?" → the UPCOMING list (scheduled events) - "What IR events did {ticker} have this year?" / "was {ticker} at any conferences?" - "What materials are attached to {ticker}'s last earnings event?" Each event has: occurred_at (issuer-local datetime) + time_precision, event_type (verbatim/open vocab), the verbatim source title, and material chips — each material's `material_id` is the get_ir_documents doc_id (a POINTER; read the content with get_ir_documents, not here). Coverage is honest: if a company hasn't been harvested yet, that is stated — an empty result does NOT mean the company has no IR events. `last_checked_at` stamps the calendar's as-of time (events announced since are not shown). For a deck's slide TEXT → get_ir_documents. For what management SAID on an earnings call (guidance/tone by quarter) → compare_earnings_calls. **Not point-in-time.** No `vantage_date` — the upcoming/past split anchors on TODAY and the calendar reflects current knowledge. For as-of / backtest work use a `vantage_date` tool: `get_filing_index`, `list_filings`, `get_earnings`, `get_financials`.
get_company_overview
Get comprehensive financial overview for a company in a single call. Includes: current price, valuation (P/E, P/B, EV multiples, PEG), profitability (revenue, margins, returns), cash flow (OCF, FCF, yields), balance sheet (debt, equity, ratios), capital allocation (buybacks, shares outstanding, shareholder yield), business segment + geographic revenue mix (latest 10-K, with YoY change), latest earnings insights, filing intelligence highlights, and company flags. Depth presets: - depth="snapshot" — headline facts only (~2K chars): title, key signals, filing signals summary, flags, latest filing pointers. Best for multi-ticker sequencing or quick health checks. - depth="core" (default) — full overview with valuation, profitability, segments, cash flow, balance sheet, capital allocation, and earnings. - depth="full" — core + all tags (no 7-tag truncation), all earnings highlights/concerns (no 3-item truncation), plus 5Y historical distribution (median/p25/p75/p90) for P/E, EV/EBITDA, EV/FCF. Latest snapshot only — use get_financials for multi-year trends, get_xbrl_facts for multi-period segment history, get_filing_index for a signal map of the latest filing, compare_companies for peer benchmarking, get_stock_price for a historical/as-of-a-date close or a return between two dates (the price here is current only). POINT-IN-TIME / AS-OF: this overview does NOT take an as-of date — every figure is the latest snapshot. For a backtest or "as of <past date>" analysis (avoiding look-ahead), do NOT read the as-of state off this tool; route to the as-of-capable tools instead: get_financials(vantage_date="YYYY-MM-DD") for the statements filed on/before that date, get_filing_section/get_filing_index(vantage_date=…) for the then-current filing text/signals, and get_stock_price for the close on/after a date. ⚠ Know the limit of the vantage tools: they bound which FILINGS are visible and which SOURCE is cited, not the VALUE — a period restated by a later filing is served at its RESTATED value under a pre-vantage citation. get_financials and get_metric_history both flag that case with an explicit LOOK-AHEAD warning, so it is disclosed rather than silent. The only true as-originally-filed series is get_xbrl_facts with period_history=true — prefer it whenever the backtest depends on what the number actually was at the time. Use search_companies first if unsure of the exact ticker.
compare
compare_companies
Compare a company against peers across ~70 curated fundamental metrics (TTM), with percentile rankings and relative strengths/weaknesses. Returns a side-by-side table covering valuation (P/E, P/B, EV/EBITDA, EV/Sales, FCF yield), profitability (gross/operating/net/EBITDA margins, ROE, ROA, ROIC), leverage & liquidity (debt/equity, net debt/EBITDA, interest coverage, current ratio), efficiency (asset/inventory turnover, DSO, cash conversion cycle), and capital returns (dividend yield, dividend payout ratio, buyback yield, shareholder yield). Sector-inapplicable metrics are omitted (e.g. gross margin / FCF leverage for banks). Pass 'metrics' to focus the table on specific metric_ids. This is a TTM cross-sectional snapshot — for a single company's value in a specific fiscal year/quarter use get_metric_history. Each company's row is dated: 'Data through' is its latest reported period, and valuation multiples are priced at the last close on/before that period end (period-end LOCF) — NOT today's price, and the dates can differ across peers by a quarter. For a multiple AS OF a specific date, or at the live price, or a CUSTOM definition (e.g. lease-adjusted EV), assemble it from get_stock_price (price leg) + get_metric_history primitives. peer_mode controls peer selection: - 'sector' (default): auto-selected from same sector + similar market cap - 'tags': auto-selected by business model similarity (tag Jaccard) — better for cross-sector comparisons Override with custom_peers for specific matchups. The number of custom_peers is capped by plan (Free: 3, Pro: 10); exceeding it returns the limit and the count you asked for, so retry with that many. Data sourced from SEC EDGAR, updated with each quarterly/annual filing. Use Cases: - "Compare AAPL vs MSFT" -> compare_companies("AAPL", custom_peers="MSFT") - "How does NVDA stack up in its sector?" -> compare_companies("NVDA") - "Dividend payout ratio: KO vs KDP/PEP/KHC" -> compare_companies("KO", custom_peers="KDP,PEP,KHC", metrics="dividend_payout_ratio,dividend_yield") - "COST vs WMT vs TGT" -> compare_companies("COST", custom_peers="WMT,TGT") Responses capped at ~20K chars. If truncated, use fewer custom_peers or a 'metrics' subset.
compare_earnings_calls
How has management's posture shifted across recent earnings calls? Cross-quarter trajectory view of transcript signals for a single ticker. This is MetricDuck's EARNINGS-CALL TRANSCRIPT tool (agents also look for this as get_earnings_call_transcript / get_earnings_transcript / get_earnings_call / search_earnings_calls). For ONE call's verbatim prepared remarks or Q&A, drill with get_filing_section(section_id="transcript_prepared_remarks" | "transcript_qa_session"); this tool gives the cross-quarter view. Different from get_filing_index (single-call triage map): this aligns calls by event date and surfaces CROSS-QUARTER patterns. For per-call depth, drill with get_filing_index. Output (coverage-dependent): a coverage table per quarter — event date, fiscal period, accession, status, and transcript Source tier (SEC-filed vs Issuer-published vs Machine-transcribed), surfacing NO_TRANSCRIPT / WAITING gaps; transcripts are management commentary, not SEC-filed XBRL facts. Then an aggregate-trajectory table (Q&A Deflection / Concerns Retained / Forward Commits — one row per scalar, one column per quarter), guidance deltas grouped by metric, and the per-quarter qualitative arrays for whichever dimensions you request, surfaced side-by-side so drift is readable across columns. Drill hints are pinned to accessions. Use Cases: - "Deflection trend?" -> compare_earnings_calls("RDDT", n_quarters=8, dimensions=["hedges", "qa"]) - "Guidance discipline shifting?" -> compare_earnings_calls("NVDA", dimensions=["guidance"]) - "Strategic priorities + KPIs drift" -> compare_earnings_calls("PG", dimensions=["priorities", "kpi"]) Sister Sources: single-call deep read → `get_filing_section` (section_id="transcript_prepared_remarks" / "transcript_qa_session"); cross-period signal changes → `screen_filing_signals` with since_date/until_date; IR press releases → `screen_filing_signals` with signal_type="ir_press_release".
earnings
get_earnings
8-K earnings-RELEASE financials — headline income statement (revenue, net income, operating income, diluted EPS) PLUS the as-released cash-flow statement (operating cash flow, capex, free cash flow, +growth), typically WEEKS before the audited 10-Q/10-K. Often the ONLY structured source for the fresh quarter's capex/OCF/FCF (the 8-K carries no XBRL, so get_financials/get_metric_history still show the prior quarter until the 10-Q lands). Distinct from get_financials (audited XBRL 10-K/10-Q — filed later, GAAP-consistent) and get_company_overview (single-period snapshot; earnings section is prose only, no figures). Use this for the earliest as-reported release figures, each with a deep-link + verbatim quote when the API has an attested receipt. Use Cases: - "What did NVDA report for its latest quarter's revenue?" -> get_earnings("NVDA") - "TSLA's last 8 quarters of earnings releases" -> get_earnings("TSLA", quarters=8) Release figures are management's own characterization and may be non-GAAP-adjacent — verify against the quote when precision matters. A figure without a receipt is still shown (often filled from a prior extraction pass or awaiting the producer's validation) but without a deep-link — absence of a receipt is not evidence the value is wrong. Point-in-time: pass `vantage_date` (YYYY-MM-DD) to serve the releases KNOWN on/before that date — the `quarters` walk back from the vantage instead of today. This bounds which RELEASES are visible, not which extraction of them (see the parameter note); unlike `get_financials`/`get_metric_history` there is no restatement look-ahead here, because a revised release is a new accession and is bounded. Sibling as-of tools: `get_filing_section`, `get_filing_index`, `list_filings`, `get_financials`, `get_metric_history`, `compare_earnings_calls` (`get_company_overview` is NOT as-of-capable — always the latest snapshot). **Exactness:** the table ABBREVIATES (`$118.70B`) — quote exact figures from `<raw_data>` instead. Capped at ~20K chars; a long response drops whole quarters, oldest first. Adjacent tools: get_financials(), get_company_overview(), get_guidance_vs_actual() to score this release's actuals against prior guidance.
get_earnings_reports
Per-fiscal-period earnings DOCUMENT INDEX — one row per quarter/year gathering the documents for that reporting period: the 8-K press release, the earnings-call transcript (with prepared-remarks / Q&A deep-links), the 10-Q/10-K, the IR presentation deck(s), and the webcast event. Each artifact is present or honestly absent, so this is the "what can I pull for this quarter, and how do I reach it" map. Reach for this to answer "what's available / where do I read it" per period: - "What documents does {ticker} have for its last earnings?" → the newest row's artifacts (press release, transcript, deck, webcast, 10-Q) - "Give me {ticker}'s earnings transcripts / decks by quarter" → the per-period transcript + deck links - "Is there a webcast / presentation deck for {ticker}'s Q2?" → that row's webcast + deck cells (honest-absent when not harvested) This is a NAVIGATION index, not figures. For the release NUMBERS (revenue / EPS / net income) use get_earnings; for audited XBRL statements get_financials; for the IR event CALENDAR (upcoming + past) get_company_events; for a deck's slide TEXT get_ir_documents; for what management SAID on the call (guidance/tone by quarter) compare_earnings_calls. Coverage is honest per cell: a transcript reads present/pending/none; a deck join is exact (fiscal-period tuple, never a date); a webcast is a single-candidate ±1d match — and when the IR calendar isn't harvested that is stated (a missing webcast is NOT "no webcast held"). The response's `claimed` set is the deck/event ids this surface owns (so an IR-card consumer subtracts them cleanly). **Not point-in-time.** No `vantage_date` — the index reflects documents as known TODAY. For as-of / backtest work use a `vantage_date` tool: `get_earnings`, `get_financials`, `get_filing_index`, `get_filing_section`, `list_filings`, `get_metric_history`, `compare_earnings_calls`.
filing
get_filing_index
Get a navigable signal index for a company's latest SEC filing. Returns typed facts extracted from the filing, each with evidence and a section pointer for drill-down. This is the "table of contents" for what's in the filing — use it to decide WHAT to read. The index is agnostic to your intent — all facts presented neutrally. Pick the facts relevant to YOUR analysis, then drill with get_filing_section(). Facts from LLM analysis are labeled as such. Optional lens parameter filters to a specific analytical view: - earnings_quality: SBC, accounting flags, material weaknesses - debt_stress: debt profile, covenant compliance, near-term maturities - risk_trajectory: risk factors, escalations, key uncertainties - competitive_position: segments, customer/channel/geographic concentration - management_outlook: tone, guidance, guidance accuracy Use this as the lightweight first-look map of what's in a filing before drilling into the text with get_filing_section. IMPORTANT — indexes only the LATEST filing. For a PRIOR quarter's operating KPIs (same-store / comparable sales, ARPU, take-rate, bookings), forward GUIDANCE, or a BEAT/MISS-vs-guidance question (e.g. "FND same-store sales in Q4 2024", "did MU beat its Q3 gross-margin guidance"), do NOT page through the latest 10-Q/10-K — those metrics live in that quarter's EARNINGS-RELEASE 8-K, which MetricDuck extracts (comparable sales, KPIs, guidance, beat/miss) per quarter. Route: list_filings(ticker, form_subtype="8-K-earnings", years=N) — each row is labelled with its implied fiscal period, so pick that quarter's accession from the list (do NOT pass fiscal_year/fiscal_period here; 8-Ks are not period-indexed), then get_filing_section(ticker, "earnings_press_release" | "earnings_income_statement" | "earnings_segment_data", accession_number=<that 8-K>). The release NARRATIVE — highlights, forward GUIDANCE/outlook, CEO commentary — lives in "earnings_press_release" (target it with query="outlook"); "earnings_document_map" is now a compact TOC (headline metrics + table/section index — call get_filing_section with accession_number and NO section_id for the outline). (compare_earnings_calls(ticker) gives the cross-quarter KPI/guidance trajectory.) Use Cases: - "What should I look at in AAPL's 10-K?" -> get_filing_index("AAPL") - "Any accounting red flags for ENPH?" -> get_filing_index("ENPH", lens="earnings_quality") - "Debt situation for BA?" -> get_filing_index("BA", lens="debt_stress") - "How is TSLA management framing things?" -> get_filing_index("TSLA", lens="management_outlook") - "FND same-store sales in Q4 2024?" (prior-quarter KPI) -> list_filings("FND", form_subtype="8-K-earnings", years=3) -> get_filing_section("FND", "earnings_press_release", accession_number=<Q4 2024 8-K>) (the narrative/guidance prose; "earnings_document_map" is the compact TOC) Sister Sources (non-SEC): - Earnings call transcripts → `compare_earnings_calls` (cross-quarter view) - IR press releases / events → `screen_filing_signals` with signal_type="ir_press_release"
get_filing_section
Read a specific section from an SEC Source (10-K, 10-Q, 8-K earnings, 8-K events, or DEF 14A proxy). **Two modes:** 1. **Section mode (default)** — pass section_id for full paginated text (up to 10 chunks per page). 2. **Outline mode** — OMIT section_id, pass accession_number: returns the filing's section TOC with ~120-char previews, so you pick by content instead of guessing an id. Use it on an unfamiliar Source (multi-exhibit 8-K, DEF 14A, FPI 6-K). Omitting accession_number reads the latest filing; `list_filings` finds a specific one. Valid ids are listed under `section_id` below. Use Cases: - "Apple risk factors" -> get_filing_section("AAPL", "risk_factors") - "Customer concentration in NVDA" -> get_filing_section("NVDA", "risk_factors", query="customer concentration") - "Workforce / headcount by geography" -> get_filing_section("MSFT", "business_description", query="human capital") - "M&A terms" -> get_filing_section("CVX", "item_1_01_material_agreement", form_type="8-K") - "As of a past date / point-in-time" -> get_filing_section("MSFT", "business_description", vantage_date="2025-04-07") (serves the latest filing on/before that date — don't assume the newest filing reflects a past vantage) - "Multi-exhibit 8-K" -> get_filing_section(ticker, accession_number="...") (outline mode) → pick exhibit → drill by section_id Sister Sources (non-SEC): - Earnings call transcripts → `compare_earnings_calls`, or list_filings + section_id="transcript_prepared_remarks" - IR press releases / events → `screen_filing_signals` with signal_type="ir_press_release"; earnings-DECK guidance / operational KPIs (in neither the filing nor XBRL) → `get_ir_documents` - Raw XBRL dimensional facts → `get_xbrl_facts` - Year-over-year risk-factor change → `screen_filing_signals(signals=["has_new_risks"], ticker=…)` — a computed vs-prior-filing signal, cheaper and more reliable than diffing two filings yourself - A figure ABSENT from the section you expected → `search_sec_filings(company=<ticker/CIK>, query="exact phrase")` locates which section of which filing carries it — absence from one section does not mean the filing lacks it **Delisted / acquired issuers**: pass `cik` (10-digit, zero-padded) instead of `ticker` and set `include_delisted=true` — e.g. SAVE Spirit Airlines (`cik="0001498710"`). Responses capped at ~20K chars. Use offset for pagination or query to narrow results.
metric
get_metric_history
Time series for one metric across fiscal periods. Returns newest-first rows with fiscal_year + fiscal_period labels — AUTHORITATIVE for period-specific questions ("Q2 FY2025?"). The period_end calendar date is NOT the fiscal label, especially for non-December FYE companies (AAPL FY ends Sep; CRM FY ends Jan; ORCL FY ends May). Each row with an SEC accession is cited back to the source filing via the MetricDuck viewer. ⚠ CONSOLIDATED ONLY — there is no segment/geography/product breakdown here, and no parameter adds one: the metrics layer sums those axes away, so per-member values are never stored. For a BY-SEGMENT series use `get_xbrl_facts(ticker, search="<segment name> revenue", period_history=true)` (as-filed dimensional facts) or `get_filing_section(ticker, "table_segment_reporting")` (the schedule, 3 fiscal years per 10-K). Use Cases: - "What was AAPL's Q2 FY2025 gross margin?" -> get_metric_history("AAPL", "gross_margin") - "ROE last 5 years for MSFT" -> get_metric_history("MSFT", "roe", period_type="FY", window=5) - "NVDA TTM revenue trend" -> get_metric_history("NVDA", "revenues", period_type="TTM") - "ABNB gross booking value trend" -> get_metric_history("ABNB", "gross_booking_value") (operating KPI; quarterly or FY) - "Net interest margin for a bank" -> get_metric_history("<bank>", "net_interest_margin") - "As of a past date / point-in-time" -> get_metric_history("MSFT", "revenues", vantage_date="2024-04-30") (series as known from filings published on/before that date) Also serves NON-XBRL operating KPIs (LLM-extracted from 10-K/10-Q MD&A + earnings releases), available QUARTERLY and ANNUAL (FY) — coverage varies by KPI. Spans banking (net_interest_margin, common_equity_tier_1_capital_ratio), insurance (combined_ratio), SaaS (arr, remaining_performance_obligations), retail/marketplace (store_count, same_store_sales, gross_booking_value, take_rate), lodging/REIT (revpar, occupancy_rate), airlines (passenger_load_factor, prasm, casm), energy (oil_production), workforce (headcount), and more — see the `metric_id` parameter for the common ids. Matching is strict (lowercase, exact spelling) and an unknown id returns the full served catalog, so guessing a canonical name is cheap. Financial-sector tickers (banks, insurers) often NULL on COGS-based metrics (gross_margin, gross_profit) — use sector-appropriate alternatives where available. Price-derived multiples here (pe_ratio, ev_ebitda, pb_ratio…) use the PERIOD-END close; for a price on a SPECIFIC date use get_stock_price. To assemble a CUSTOM multiple (e.g. EV including operating leases) combine get_stock_price (price leg) with get_metric_history primitives: oper_lease_liabs, ttl_debt, cash_st_invs, ttl_equity, shares_basic. **Latest fiscal year during earnings season:** full-year results post in an earnings 8-K weeks before the 10-K, which is what populates this structured FY series. If you query the latest FY inside that gap, the series ends one year early — this tool then appends a pointer to the earnings 8-K; follow it (get_filing_section "earnings_income_statement") rather than concluding the year is unavailable. Adjacent tools: get_company_overview for a single-period snapshot across many metrics; get_financials for full statements (all line items) across multiple periods; get_stock_price for daily share prices and period returns.
get_metric_lineage
The DERIVATION of one COMPUTED metric — its human formula + immediate inputs (each value + source), one level at a time. The audit / verify affordance for derived figures (margins, ratios, ROIC, FCF, adj-EBITDA): call it ONLY when the query asks **how a metric is computed**, **which definition** MetricDuck used, or to **verify / audit** the derivation — NOT to get the value itself (use get_metric_history / get_company_overview for that). Drillable (lazy, one level per call): - a `derived` input points to its OWN derivation — call get_metric_lineage(ticker, that_symbol) to go deeper. - a `base` input is an as-filed XBRL fact — open its filing handle, or get_xbrl_facts(ticker, search="<symbol>") to land on the exact fact. Use Cases: - "How is AAPL's net_margin calculated?" -> get_metric_lineage("AAPL", "net_margin") - "Which ROIC definition does this use?" -> get_metric_lineage("AAPL", "roic") - "Audit / verify gross_margin for Q2 FY2025" -> get_metric_lineage("AAPL", "gross_margin", fiscal_year=2025, fiscal_period="Q2") Computed metrics only — a base as-filed figure has no derivation (the tool says so and points to get_xbrl_facts).
screen
screen_companies
Screen 5,500+ US companies by financial metrics. Find stocks matching quantitative criteria. Metric IDs (canonical names from filing_metrics): - Valuation: pe_ratio, pb_ratio, ev_ebitda, fcf_yield, market_cap, ev - Profitability: gross_margin, oper_margin, net_margin, ebitda_margin, roe, roa, roic - Cash Flow: fcf, net_cf_ops, cash_conversion - Balance Sheet: debt_to_equity, current_ratio, ttl_debt, ttl_equity, cash_st_invs - Size: revenues, net_income, ebitda, gross_profit Growth screening: set period_type — e.g. metric_id="revenues" with period_type="ttm.yoy" (YoY). Growth pairs served: revenues/net_income/eps_basic/eps_diluted/fcf/roic @ ttm.yoy, revenues/fcf @ ttm.cagr3, ttl_assets @ ss.yoy. Period types: ttm (default), ss (balance sheet snapshot), the growth pairs above, and q.med8/q.trend8/q.stdv8 valuation-quality series (pe_ratio, ev_ebitda, ev_fcf, roic). The screener serves LATEST-snapshot values; an unsupported metric+period combination returns a 422 naming the supported set — for other periods or full history use get_metric_history. Sectors: TECH, FIN, HEALTH, CONS_STAPLES, CONS_DISC, IND, ENERGY, UTIL, RE, MAT, COMM Operators: gt (>), gte (>=), lt (<), lte (<=), eq (=), between Tag filtering (required_tags / excluded_tags) selects by business-model classification; unclassified companies are excluded from tag-filtered results. Note: margins, returns and ROIC are decimals (0.15 = 15%). Negative P/E means losses — add a gt(0) filter to exclude loss-makers. Use Cases: - "High ROIC tech stocks" -> filters=[{metric_id:"roic", operator:"gt", value:0.15}], sectors=["TECH"] - "Undervalued profitable industrials" -> filters=[{metric_id:"pe_ratio", operator:"lt", value:15}, {metric_id:"pe_ratio", operator:"gt", value:0}], sectors=["IND"] - "Revenue growing >10% YoY" -> filters=[{metric_id:"revenues", operator:"gt", value:0.10, period_type:"ttm.yoy"}] - "AI infrastructure companies not exposed to China supply chain" -> required_tags=["ai_ml_infrastructure"], excluded_tags=["china_supply_chain_heavy"] - "Profitable subscription businesses" -> filters=[{metric_id:"net_margin", operator:"gt", value:0.10}], required_tags=["subscription_recurring"] To screen by filing SIGNALS (tone, covenant risk, material weakness, etc.), use screen_filing_signals — a universe-correct cross-company signal screen — then intersect with a metric screen here. Responses capped at ~20K chars. If truncated, reduce limit or add stricter filters.
screen_filing_signals
Screen companies by signals across all source types — filings, earnings, transcripts, IR events. This is NOT metric screening (use screen_companies for P/E, ROIC, etc.). Screens by verifiable facts, not LLM-generated scores. Signals span five source types — 10-K/10-Q filing intelligence, 8-K/6-K earnings releases, earnings-call transcripts, IR press releases, and DEF 14A proxies. Full id catalog with labels: see the `signals` parameter. Use Cases: - "Which tech companies have cautious management?" -> signals=["tone_cautious"], sectors=["TECH"] - "Does NVDA have any tone_shifted recently?" -> ticker="NVDA", signals=["tone_shifted"], recency_days=30 - "Did AAPL disclose new risk factors vs last year's 10-K?" (year-over-year risk surveillance) -> ticker="AAPL", signals=["has_new_risks"] — prefer this over reading risk_factors for two periods via get_filing_section and diffing the prose by hand - "Companies that gave specific guidance on calls?" -> signals=["transcript_has_guidance"] - "Which companies announced strategic partnerships or M&A deals?" -> signals=["ir_partnership"] Cross-filing composition (Brief 35 — Pattern 4): `ir_partnership` matches on M&A / partnership 8-K anchors (Item 1.01) carry a `companion_accessions: string[]` field in their payload value when the announcement is split across an anchor + same-day companion 8-K (7.01 Reg FD + Ex 99 press release / 8.01 other events). To read the full announcement narrative — CEO quotes, deal terms, investor-presentation text living in the companion — pass those accession numbers to `get_filing_section({..., section_id:"item_1_01_material_agreement", include_companions:true, companion_accessions:[...]})`. Empty list means no companion exists or the producer hasn't backfilled it (acceptable; anchor-only flow still works).
browse
browse_company
Entity-axis navigation primitive — an orientation map for one company. Returns a single response containing identity (incl. CIK), the text-extracted filing inventory by form type (the subset with extracted section text — NOT the company's full SEC filing history; use `list_filings` for the complete registry incl. filed-but-unextracted rows), **signal availability inline**, indexed range, and ranked drill-down pointers — so one call tells you which signals fire for the company and which axis to descend next (signal-axis, source-axis, or metric-axis). Accepts a ticker, a company name, or a CIK, so it also resolves the entity. Compared with `search_companies`: that one is the resolver — it matches a name or partial name across companies and carries the SEC EDGAR entity link, filer_type, fiscal year-end and former names. Use it to pick between candidates; use this when you already know the company and want its inventory. **When to use:** - Starting a research thread on a single company - Confirming what data MetricDuck has indexed before deep-diving - Discovering which signals fire (M&A, partnerships, guidance shifts, accounting flags) without needing to fetch a filing first **When NOT to use:** - Cross-company screening → use `screen_companies` (metrics) or `screen_filing_signals` (signals) - Concept/theme discovery → use `search_sec_filings` **Drill-down map (the response will recommend specific calls based on what's available):** - `get_filing_index(ticker)` — full signal map for the latest filing - `get_xbrl_facts(ticker, search="...")` — dimensional financial drill-down _(atom v1: revisit response shape after first 5 q001/q012/q003 traces)_
companies
search_companies
Resolve a company name or ticker to the exact ticker symbol via fuzzy name/ticker match. **Scope:** exact-entity lookup only. Handles partial names ("micro" -> MSFT), typos, and ticker variations. Returns ticker, full name, CIK, SIC, filer type (domestic / foreign private issuer / fund — i.e. which form family to expect), fiscal year-end, and a primary-source SEC EDGAR entity-page link (verify the resolution + see the company's full filing history) for each match. **Use this when:** you have a specific company name or ambiguous ticker and need to confirm the exact ticker before calling other tools. **Delisted / renamed / acquired companies** are resolvable by current OR former name (e.g. "American Software" → Logility, "Chase Manhattan" → JPM). They are returned ranked below active matches, flagged `[delisted]`, with their CIK. They have no current ticker — pass the returned `cik` to downstream tools (company tools accept a CIK in place of a ticker, except `get_stock_price`, which needs a ticker). **Input tip:** queries matching the pattern of 2-5 uppercase letters are auto-extracted as a ticker. If you pass an all-caps company name (e.g., "AMCOR") that is NOT a ticker, the lookup may miss — pass "Amcor" with normal casing to force name-search behavior. On miss, this tool returns suggested near-matches when possible. **Do NOT use this for concept/theme/industry discovery** (e.g., "gold miners", "LNG exposure", "companies mentioning tariffs"). This tool matches on company-name text only — it cannot surface companies by what they do. For concept discovery, use `search_sec_filings` (full-text search across filings) or `screen_companies` (metric + sector filters). **Coverage boundary:** MetricDuck is **SEC-EDGAR only**. This tool is the authoritative coverage check. A no-match on a **non-US local-exchange symbol** (e.g. `3087.T`, `LSE:HSBA`, `7203:JP`) is a coverage boundary, not a lookup miss — the tool says so explicitly and you should treat it as **terminal** (don't retry ticker variations). Foreign issuers that file a US 20-F/40-F (HSBC, Toyota, Novo Nordisk…) ARE covered — reach them by **company name**, not their local symbol.
documents
get_ir_documents
Retrieve IR earnings-PRESENTATION-DECK text — forward guidance, operational KPIs, and segment outlook that are ONLY in the company's investor-relations slide deck and NOT in the SEC 8-K/10-Q release text or XBRL. Reach for this when the answer is a forward-looking guidance range or an operational KPI that the structured tools miss: - get_metric_history / get_xbrl_facts return no series for a KPI or guidance figure - get_filing_section finds the 8-K earnings release but it lacks the guidance/KPI (decks are a separate exhibit/source) What lives here (not in XBRL/filing text): production or revenue guidance ranges, segment/division outlook, operational KPIs presented as slide charts (e.g., berth capacity %, Mboed production guidance, adjusted-EBITDA guidance). Use Cases: - "OXY Q3 2024 production guidance" -> get_ir_documents("OXY", fiscal_year=2024, fiscal_period="Q3", query="production guidance") - "NCLH berth capacity outlook" -> get_ir_documents("NCLH", fiscal_year=2021, fiscal_period="Q3", query="berth") - "KNTK adjusted EBITDA guidance range" -> get_ir_documents("KNTK", fiscal_year=2023, fiscal_period="Q3", query="EBITDA") Each deck returns its title, original IR url, a stable MetricDuck-hosted gcs_uri, and the matching slide text cited by page. Pass a `query` to land on the exact page; omit it for a bounded prefix of the latest deck. Resolve by ticker or cik; narrow with fiscal_year/fiscal_period.
filings
list_filings
Browse Sources inventory and the section catalog for a single company. Covers SEC filings: 10-K, 10-Q, 8-K, DEF 14A, plus 20-F / 40-F / 6-K for foreign private issuers. **Scope:** filings-metadata utility. Returns filing list (form type, dates, accession numbers) plus per-section details (word count, chunk count, tables) for 10-K/10-Q/DEF 14A; 8-K returns filing metadata only. Default: last 2 years. Use `fiscal_year` + `fiscal_period` to pin a single historical PERIODIC filing (10-K/10-Q) in one call — 8-K sub-types are not period-indexed, so pair `form_subtype` with `years` instead. **For signal triage and "what matters" in a filing, use `get_filing_index` instead.** Use `list_filings` only when: - You need an accession_number for a specific historical filing (before `get_xbrl_facts` or `get_filing_section`) - You need to pin a specific fiscal year/period (e.g., FY2020 Q3) - You need the full section inventory with sizes to plan pagination - You need to confirm whether a specific filing exists Sister Sources (non-SEC): earnings call transcripts → `compare_earnings_calls`; IR press releases / events → `screen_filing_signals` with signal_type="ir_press_release". **Delisted / acquired issuers**: pass `cik` (10-digit, zero-padded) instead of `ticker` and set `include_delisted=true`. SEC's ticker registry excludes delisted issuers, so `ticker`-only calls 404 even when MetricDuck holds the filings. Example: SAVE Spirit Airlines (`cik="0001498710"`). Data horizon: 2013+. Responses capped at ~20K chars; narrow via `form_type`, `fiscal_year`, or reduce `years`.
financials
get_financials
Get multi-period financial statements: income statement, balance sheet, and cash flow in one call. Returns quantitative historical data with key metrics and trends. Default: all 3 statements, quarterly, 2 years. For qualitative analysis (risks, accounting quality, management tone), use get_filing_index (signal map) then get_filing_section to read the text. Use Cases: - "Show me AAPL's financials" -> all statements - "MSFT revenue trend 5 years" -> period="annual", years=5 - "Is Tesla's debt increasing?" -> statements=["balance"] - "As of a past date / point-in-time" -> get_financials("MSFT", vantage_date="2024-04-30") (values as known from filings published on/before that date) Each period cites its original disclosing SEC filing (accession + filed date in a footnote; resolvable EDGAR index handles in the `<raw_data>` block), so every figure is traceable to its source filing. **Exactness:** the markdown table ABBREVIATES (`$68.14M`) — it quantises to $10K above $1M and $10M above $1B, so it is not a tie-out surface. The `<raw_data>` block carries the exact stored value (`68135000`). Quote figures from `<raw_data>`, not the table, whenever the precise number matters. Responses capped at ~20K chars. If truncated, whole statements are dropped (not sliced) with a note — request fewer statements or reduce years. Note the cap also trims `<raw_data>` periods, so a truncated response can lose the exact channel for the dropped periods.
guidance
get_guidance_vs_actual
Did management deliver what they guided? Joins forward guidance from earnings-call transcripts to reported actuals from 10-K/10-Q + 8-K earnings for the same ticker + fiscal period. Returns both sides verbatim with quotes and locators — agents synthesize the delivered-vs-guided narrative. This is a cross-feed temporal join; no single feed answers this question. Use Cases: - "Did NVDA deliver on Q2 FY2026 guidance?" -> get_guidance_vs_actual("NVDA", fiscal_period="Q2 FY2026") - "How disciplined has MSFT been against its own guidance?" -> get_guidance_vs_actual("MSFT") then compare across periods - "Latest period's guidance-vs-actual" -> get_guidance_vs_actual("TSLA") (period defaults to most recent) Returns everything a beat/miss verdict needs — never the verdict. The comparison is basis-matched, as-reported-only arithmetic; the CALLER applies valence (whether "above guidance" is good is the caller's judgment, not MetricDuck's). Use Cases: - "Did NVDA deliver on Q2 FY2026 guidance?" -> get_guidance_vs_actual("NVDA", fiscal_period="Q2 FY2026") — read range_position (above/within/below) + delta and decide yourself. Output: - Guidance: forward items targeting the period — from earnings-call transcripts AND 8-K earnings releases (metric, value/range, basis, period, verbatim quote, source). - Actuals: SEC 10-Q/K metric + narrative signals for that period, plus 8-K earnings signals when present. - Comparison: for each guidance item, when it can be recomputed from the receipts on its OWN basis (GAAP vs non-GAAP matched, units aligned, period settled) — a neutral `range_position` (above | within | below the guided band) + signed `delta`. Otherwise a typed `status` says why NOT (no_actual_on_basis / not_yet_settled / value_unparsed / period_unresolved / value_incongruent) — never a false or guessed verdict. A non-GAAP guide is never compared to a GAAP actual. - Notes: counts of calls/filings covered + comparison statuses so agents know coverage depth before interpreting. **Not point-in-time.** No `vantage_date` — guidance↔actual joins reflect everything stored as of TODAY (a backtest at a past date would see actuals that had not yet been reported). For as-of work use a `vantage_date` tool: `get_earnings`, `get_financials`, `get_filing_index`, `compare_earnings_calls`.
recent
list_recent_filings
Discover recent SEC filings landed since a watermark — single call, universe-wide. **Use this when:** building event-driven agent workflows (Routines, alerts, daily portfolio checks). The right primitive when the question is "what new filings have landed?" rather than "what filings does this one company have?". **Returns:** flat list of {ticker, accession, filed_at, form_type, form_subtype}, newest filing date first and **largest issuers first within a date** — so `limit=15` during earnings week surfaces the banks and mega-caps that filed, not the alphabetically-first micro-caps. `form_subtype` is computed from the filing's section inventory (the four values are spelled out under `form_subtypes`); null for non-8-K forms. **Portfolio filter:** `tickers` (plural, an array); `ticker="TSM"` is accepted as an alias. Both given = union, cap 50. **Cost:** ~one call regardless of portfolio size — vs O(N) calls if you fan out per-ticker via `list_filings`. **Composition:** for each row, drill in via `get_filing_section(ticker, accession_number=...)` — omit `section_id` for that filing's section outline, then pass a `section_id` for narrative content. **Use `list_filings` instead when:** you need ALL filings for ONE company (paginate by year) — that is the per-company catalog; this is the cross-company / event-discovery primitive. **Not point-in-time.** No `vantage_date` — the watermark walks the live discovery feed as of TODAY. For an as-of view of one company's filings use `list_filings` with `vantage_date`.
sec
search_sec_filings
Search the full text of every SEC filing since 2001 to find companies related to any concept — a product, technology, regulation, event, or company. Returns filing-level results with aggregated statistics (company count, form type breakdown, industry distribution). For 10-K/10-Q filings processed by MetricDuck, also shows WHICH SECTIONS contain the term with drill-in pointers. **Searchable form types** — any SEC form since 2001; omit `form_type` to search all: - Periodic reports: 10-K, 10-Q (section-level drill-down available), 20-F, 40-F, 6-K (foreign private issuers) - Events + proxies: 8-K, DEF 14A / DEFM14A / PRE 14A - Registration + offerings: S-1, F-1, S-3, S-4, 424B series - Ownership + other: SC 13D, SC 13G, SD (conflict minerals), N-CSR / N-CSRS (fund reports) **Section-level enrichment** (10-K/10-Q only): results name which sections contain the term, with chunk pointers for drill-in via get_filing_section. Other forms return filing metadata + accession numbers only. Use cases: - "Who supplies Apple?" → query="\"Apple Inc.\"", form_type="10-K,10-Q,8-K" → Company Exposure Map of the filers mentioning Apple. Constrain forms — see the fund-noise note below. - "What did WM say at its investor day?" → query="\"investor day\"", company="WM" → that filer only - "Recent data breaches?" → query="cybersecurity incident", form_type="8-K" - "Tariff-exposed companies?" → query="tariff", form_type="10-K" → risk factor disclosures - "Activist campaigns?" → query="board representation", form_type="DEF 14A,SC 13D" When to use other tools instead: - You already know the company → `get_filing_index` (signal triage) or `list_filings` (filing inventory) - You want financial metrics → `screen_companies` (numeric filters) - You want earnings call cross-quarter view → `compare_earnings_calls` Key limitation: keyword matching only, not semantic. "No material weakness" matches "material weakness found." Verify hits with `get_filing_section` for context. Search tips: quoted exact phrases ("material weakness"); proximity `NEAR(5)`; `OR` / `NOT`; trailing wildcards (`restructur*`). **Historical event queries** (M&A announcements, lawsuits, restructurings, leadership changes): the default 1-year `date_from` and `rank_by="date"` ordering bury historical anchors under mutual-fund NPORT-P holdings. For specific events, prefer `form_type="8-K"` + widen `date_from` to before the event + `rank_by="relevance"` — this surfaces the anchor 8-K in the top results instead of fund noise.
stock
get_stock_price
Daily end-of-day stock prices (open/high/low, close, split- & dividend-adjusted adj_close, volume) for US exchange-listed companies. Sourced from a market-data feed, not SEC filings. Markets are open only on business days, so rows exist ONLY for trading days — the data IS the trading calendar: - Price ON OR AFTER a date (e.g. an announcement landing on a weekend): pass start_date=<date>; the FIRST row is that date or the next open day. - Price ON OR BEFORE a date: pass end_date=<date>; the LAST row is that date or the prior open day. - A single specific date: pass start_date=<date> (omit end_date) — returns a short forward window whose first row is your on/after price. Use Cases: - "AAPL close on 2025-07-28" -> get_stock_price("AAPL", start_date="2025-07-28") (first row = that day or next open day) - "DKNG total return 2025-01-02 → 2026-02-27" -> TWO calls: get_stock_price("DKNG", start_date="2025-01-02") and get_stock_price("DKNG", end_date="2026-02-27"); take each first/last close and compute the return (cheaper than one 14-month window) - "SUI 1/14/30 calendar days after an 8-K date" -> get_stock_price("SUI", start_date="<announce>", end_date="<announce + ~32d>"), then pick the first row on/after announce, +1, +14, +30 - "Latest price" -> get_stock_price("AAPL") When the window spans ≥2 trading days, the response also reports the first/last close and the period return on BOTH close (literal point-to-point) and adj_close (split/dividend-adjusted — the true economic return; the two diverge across a split or dividend). Each response also includes the latest REPORTED period-end shares outstanding on/before your end date (period-end balance-sheet count; dei cover where absent) plus the implied market cap at the latest close — use these for market-cap / EV / P/B math instead of deriving share counts from NI/EPS (that yields weighted-average shares, a different basis). Coverage: ~8,400 US common-equity tickers, end-of-day only (no intraday/real-time, no options/FX). Recent history is dense; deep pre-2014 history may be sparse. For period-end valuation multiples (P/E, EV/EBITDA, P/B) use get_metric_history; to assemble a CUSTOM multiple (e.g. lease-adjusted EV) combine this price with get_metric_history("ticker","oper_lease_liabs" / "ttl_debt" / "cash_st_invs" / "ttl_equity" / "shares_basic").
xbrl
get_xbrl_facts
Raw XBRL facts from SEC filings — use only when `get_financials` cannot answer the question. **Scope:** escape-hatch for dimensional / industry-specific / as-filed numbers. ~3,000 facts per filing with dimensional breakdowns (segment, geography, product line). Search by human-readable label, not XBRL concept names. **First try `get_financials`** — 323+ standard metrics across TTM/FY/Q + YOY/CAGR for all 5,500+ companies: faster, cheaper, more portable across tickers. **Use `get_xbrl_facts` only when:** - You need a segment / geographic / product-line breakdown that `get_financials` aggregates away — available only for concepts the filer XBRL-tags dimensionally (usually revenue + segment profit / Adjusted EBITDA). Segment **costs** are frequently NOT tagged; a relaxed-search miss returns the recipe for recovering them. - You need **revenue concentration / share** by customer, channel, distributor, geography, or product — the as-filed `ConcentrationRiskPercentage` facts. Deterministic, and present even when the prose only describes the relationship qualitatively. Search `concentration`. - You need an industry-specific metric not in the standard catalog (e.g., `medical cost ratio` for a health insurer, `reserve replacement ratio` for an oil & gas name) - You need to verify a specific number from filing text against the as-filed XBRL value - You need a historical fiscal year not returned by `get_financials` (pass `fiscal_year`) - You need a cash-flow / income **line across periods to de-cumulate a standalone quarter** — the as-filed cash-flow statement is cumulative YTD. Set `period_history: true` (see that parameter for the subtraction recipe). **Sign — read this before quoting a direction.** `<raw_data>.value` is the raw as-filed XBRL instance value. It is a positive magnitude for outflow / contra-asset concepts (`PaymentsTo…`, capex, accumulated depreciation) but is **signed by construction** for the `IncreaseDecreaseIn…` working-capital family. The table shows that value, except where the instance value is negative AND carries the negated-label role — there it shows the filed face instead (so a working-capital *decrease* reads as the positive source of cash the statement shows). `(filed −)` is a **best-effort hint, not a guarantee**: it comes from the filing's label linkbase and is recorded PER CONCEPT, so it fires on every use of a concept that is presented negatively *anywhere* in that filing — including lines the filing presents positively. Real example: Texas Instruments tags `IncomeTaxExpenseBenefit` with a negated label in its AOCI reclassification table, so its income-statement "Provision for income taxes" carries `(filed −)` even though the statement face reads `709`, not `(709)`. **So: trust the value, treat the flag as a prompt to check.** When direction is load-bearing, confirm against the `edgar` fact link — or use `get_financials`, which applies a curated statement-sign map instead of the linkbase flag. **Exactness:** the markdown rounds for readability; the `<raw_data>` block carries each fact's EXACT value + `decimals` (the as-filed precision floor: −3 = thousands, −6 = millions) + `edgar` — a deep-link to that exact fact in the SEC EDGAR iXBRL document, so every value resolves to the independent primary source. **Share counts (pick the right basis):** the **dei** `EntityCommonStockSharesOutstanding` (shown as "cover-page / current") is the most-current shares outstanding, as of the filing/cover date — use it for **market cap, equity value, and "shares outstanding from the cover page"**. The **us-gaap** `CommonStockSharesOutstanding` is the **balance-sheet period-end** count (an earlier date); `WeightedAverageNumberOf…SharesOutstanding` is the **per-period average for EPS**. These can differ a few % for buyback-heavy / recently-issuing filers — match the as-of date in the Period column to your task. Searching: commas OR-match (`revenue,product`); SPACES WITHIN a term AND-match, across the concept name, its label, and the filer's own dimension axis/member labels. A multi-word search is therefore a filter on the FILER's wording, not on meaning — it can drop the exact series you want with no warning. Start with ONE word and narrow client-side. Responses cap at ~20K chars — over it, whole facts are paged out of BOTH the table and the `<raw_data>` block together (the JSON stays valid) with an explicit `facts_omitted` count; narrow the search for the rest. **No `vantage_date`** — the DEFAULT path resolves the latest filing as of TODAY. A past filing IS exactly reachable: pin it with `accession_number` (from `list_filings`, which takes `vantage_date`) or `fiscal_year`/`fiscal_period` — pin the filing rather than assuming latest for as-of work.

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MetricDuck — Financial Analysis — questions

Answers built from our own checks of this server.

What can MetricDuck — Financial Analysis do?
It exposes 22 tools, read directly from the server on our last check. Among them: browse_company, compare_companies, compare_earnings_calls, get_company_events, get_company_overview, get_earnings and 16 more. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README. How MCP servers expose tools in the first place →
What is MetricDuck — Financial Analysis mostly used for?
Its tools cluster around company, filing and screen. That is what this server is built to work with — the grouping comes from the actual tool names, not from a category we assigned.
Is MetricDuck — Financial Analysis working right now?
We send a real MCP handshake every 15 minutes. Over the last 24 hours 88 of 91 checks got a reply (96.7%), average response time 227 ms. The bar chart above shows every period we have measured.
How do I connect MetricDuck — Financial Analysis?
Copy the ready config from this page — we generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each with the file path that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.
Does MetricDuck — Financial Analysis need an API key?
No. MetricDuck — Financial Analysis completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 22 of them are readable on this page. This is what we observed, not what the docs claim.
How fast is MetricDuck — Financial Analysis?
It answers our handshake in 227 ms on average, which is faster than 64% of all working MCP servers we measure. The comparison comes from our own checks across the whole registry, every 15 minutes.