Secedgar MCP Server

Find companies and retrieve entity info with optional recent filings. Entry point for most EDGAR workflows — resolves tickers, names, or CIKs to entity details, with accession numbers in the result feeding secedgar_get_filing for document content. When a date or form filter carries the scan past the recent submissions window, the full filtered filing history is also staged as df_<id> — inspect it with secedgar_dataframe_describe, then analyze it with secedgar_dataframe_query.

Compare 2-10 named companies across 1-8 XBRL concepts, aligned on calendar periods. This is the middle shape between secedgar_get_financials (one company, one concept, full history) and secedgar_fetch_frames (one concept, one period, every reporting company) — reach for it when the question names the companies. One companyfacts read per company, resolved through the same frame dedup and tag priority as secedgar_get_financials so the numbers agree. Balance-sheet and entity-info concepts are filed as point-in-time values and align on the calendar year (annual) or quarter (quarterly) their snapshot falls in, so they sit in the same matrix as income-statement lines. The inline matrix covers the most recent periods up to `periods`, trimmed further when companies x concepts x periods is too large to return in one response; the full aligned series is materialized as df_<id> for growth rates and spreads — inspect it with secedgar_dataframe_describe, then analyze it with secedgar_dataframe_query. A company that fails to resolve is reported in failed_companies and the comparison proceeds with the rest, and a company that does not report a concept is reported in gaps with the tags that were tried — never interpolated or zero-filled. Off-calendar filers and unit mismatches are surfaced in caveats rather than silently mixed.

List the dataframes (df_XXXXX_XXXXX) registered by the data-returning secedgar_* tools — any tool whose response carries a `dataset` handle stages its full result set here. Each entry surfaces source tool, query parameters, creation/expiry timestamps, row count, column schema, and whether the dataframe is truncated relative to the upstream source. Read the column schema here before writing SQL for secedgar_dataframe_query.

Run a single-statement SELECT against the canvas dataframes registered by the data-returning secedgar_* tools — any tool whose response carries a `dataset` handle. Inspect a dataframe with secedgar_dataframe_describe first; its column schema is what the SQL has to match. Read-only: writes, DDL, DROP, COPY, PRAGMA, ATTACH, and external-file table functions are rejected. System catalogs (information_schema, pg_catalog, sqlite_master, duckdb_*) are denied — list dataframes via secedgar_dataframe_describe. Optional register_as chains the result as a new dataframe with a fresh TTL.

Fetch SEC XBRL frames for one concept × one period across all reporting companies. Inline response returns a page of the ranked companies — start at the top or pass offset/next_offset to walk further down the ranking; the full frames response (all reporters) is materialized as df_<id> when a canvas is available — inspect it with secedgar_dataframe_describe, then analyze it with secedgar_dataframe_query. Accepts friendly names like "revenue" or "assets" (discover via secedgar_search_concepts) or raw XBRL tags. One call hits one XBRL tag — when a friendly name maps to multiple same-meaning tags, the response's `unqueried_tags` lists the others; call again per tag and UNION/COALESCE in SQL with an analysis-specific priority (e.g. SalesRevenueGoodsNet is goods-only). The response's `related_tags` separately flags alternate-DEFINITION tags a meaningful share of filers use as their primary line (e.g. cash incl. restricted cash, equity incl. noncontrolling interest) — a whole-universe screen on the base tag silently omits those filers; query them separately, but do not blindly union (the semantics differ). Response includes `value_distribution` and `period_end_range` to flag XBRL scale-factor anomalies and fiscal-year mixing.

Find which institutional managers reported holding an issuer, by searching 13F-HR information tables for one reporting quarter. This is the reverse direction of secedgar_get_institutional_holdings: that tool takes a manager and returns its portfolio, this one takes an issuer and returns its managers — pass a returned filer_cik plus the same quarter to read the actual position. Searching by cusip is the precise path, matching the identifier the information table itself carries; without it the issuer name is matched as a phrase against the filing text, which both over-matches (unrelated issuers sharing a word) and under-matches (managers writing the name differently), so prefer cusip whenever one is known. A CUSIP cannot be derived from a ticker here — read one off any 13F information table returned by secedgar_get_institutional_holdings. The returned list is unranked: the search index scores by text relevance, which carries no signal about position size, and no ordering by shares or market value is available without opening each filing. Managers holding under $100M in 13(f) securities are exempt from filing at all. When more managers match than fit inline, the full fetched set is staged as df_<id> — inspect it with secedgar_dataframe_describe, then analyze it with secedgar_dataframe_query.

List the 5%-and-over beneficial owners of a public company, parsed from the structured SCHEDULE 13D and SCHEDULE 13G filings made about it. The input is the ISSUER — the company being held — which is the opposite direction from secedgar_get_institutional_holdings, where the input is the manager. 13D is the activist form and carries the filer's stated purpose of the transaction; 13G is the passive form and has no purpose field at all, which is the substantive difference between a stake that intends to influence control and one that does not. Every filing is returned with each reporting person listed separately, because voting power, dispositive power, and percent of class are reported per person even on a joint filing where several funds and their controlling principal report overlapping shares — summing those percentages double-counts the same position. Coverage starts at 2024-12-18, when SEC replaced the legacy SC 13D / SC 13G text filings with this XML format; earlier stakes are readable but not parseable, and the response reports how many of them the issuer has. The full parsed set is materialized as df_<id> when a canvas is available, one row per reporting person, so it joins against the insider and 13F dataframes on issuer CIK — inspect it with secedgar_dataframe_describe, then analyze it with secedgar_dataframe_query.

Fetch a specific filing's metadata and document content by accession number. Returns the primary document as readable text. Use offset/next_offset for multi-page access to large filings (10-K, S-1 can exceed 1M chars): pass the next_offset from a truncated response to read the next page. Use section to jump directly to a heading (e.g. 'risk factors', 'item 7') without needing an offset.

Get historical XBRL financial data for a company. Accepts friendly concept names (e.g., "revenue", "net_income", "assets") or raw XBRL tags. Discover available friendly names with secedgar_search_concepts. Handles historical tag changes and deduplicates data automatically. The full series is also staged as df_<id> when a canvas is available — inspect it with secedgar_dataframe_describe, then analyze it with secedgar_dataframe_query.

List what an ETF or mutual fund holds, parsed from the NPORT-P portfolio report it files with the SEC every quarter. The input is the fund — a ticker like VOO, a fund series ID, or the registrant trust — which is the opposite direction from the ownership tools: secedgar_get_institutional_holdings and secedgar_find_holders answer who owns a company, this answers what a fund owns. Each position carries the security name, CUSIP/ISIN/LEI where the filer reports them, share balance, market value in USD, and percent of the fund's net assets, alongside fund-level net assets and total assets. Positions are returned largest-first by percent of net assets, one page of limit rows starting at offset; the full report registers as df_<id> when a canvas is available — inspect it with secedgar_dataframe_describe, then analyze it with secedgar_dataframe_query, which is how a fund running to thousands of positions is aggregated or joined against the 13F and insider dataframes. An NPORT-P covers exactly one fund series and a registrant trust files one report per series, so a trust with several funds needs the specific fund named — pass its ticker or series_id. Reports publish roughly two months after the period they cover, so every result is dated: the holdings are the portfolio as of report_period_date, not as of today.

Fetch Form 4 insider transactions (purchases, sales, grants, exercises) for a company by parsing SEC EDGAR ownership XML. Returns the reporting person, their relationship to the issuer, transaction date, type, shares traded (absolute magnitude), direction (acquire/dispose), price per share, and shares owned after the transaction. Covers nonDerivative transactions (open-market buys/sells, gifts) and derivative transactions (option exercises, RSU vests). When a canvas is available, the full set of transactions parsed from the scanned recent filings is materialized as df_<id> (the inline list is a preview capped at limit) — inspect it with secedgar_dataframe_describe, then query it with secedgar_dataframe_query to aggregate net buy/sell by insider: SUM(CASE WHEN direction='dispose' THEN -shares_traded ELSE shares_traded END). Use secedgar_search_filings with forms=["4"] for broader date-range queries or to search across all companies.

Fetch 13F-HR quarterly institutional holdings by parsing the SEC EDGAR information table XML. ticker_or_cik is the institutional filer — its 10-digit CIK (e.g. 0000102909), or an entity name resolved through EDGAR entity search — and the tool returns what that institution holds. A name that matches several EDGAR filers (some legal names are shared across entities) returns those candidates so you can retry with the exact CIK, rather than guessing. For the reverse direction — which institutions hold a given portfolio company — use secedgar_find_holders, whose filer_cik results feed straight back into this tool. The 13F information table lists each position: issuer name, CUSIP, shares held, market value (in whole USD), and put/call designation for options. Sub-lines for the same security are consolidated into distinct positions sorted by value by default (set consolidate=false for raw filing rows). The inline holdings list is one page of limit rows starting at offset — pass the returned next_offset to walk further down a large information table. The full parsed holdings set is also materialized as df_<id> when a canvas is available — inspect it with secedgar_dataframe_describe, then query it with secedgar_dataframe_query to aggregate the whole filing or self-join across quarters on cusip + reporting_period. Institutions with less than $100M in 13(f) securities are exempt and may not file. Use secedgar_search_filings with forms=["13F-HR"] for broader search.

Retrieve a company's 8-K filings with their item codes decoded, optionally filtered to specific items. 8-K item codes are how material events are actually scoped — 1.01 material agreements, 2.02 results of operations, 4.02 non-reliance on previously issued financials, 5.02 officer and director departures — and filtering by them is narrower than any form-level filter in secedgar_search_filings or secedgar_company_search, neither of which can see items. Each row carries the accession number and primary document for secedgar_get_filing; press releases usually ride as EX-99 exhibits rather than in the primary document. Two numbering regimes exist: filings from 2004-08-23 onward use the x.xx codes, earlier ones use single integers (12 was the old results-of-operations item, 9 the old Regulation FD item), and both are accepted as filters and decoded in the response. A date window reaches filings older than the recent submissions window by paging into the archive. The full filtered set is materialized as df_<id> for item-distribution analysis over time — inspect it with secedgar_dataframe_describe, then analyze it with secedgar_dataframe_query.

Build a company financial profile in one call: the latest value of every supported XBRL concept, grouped by statement. Reads the filer's complete companyfacts payload once rather than one request per concept, so it replaces a run of secedgar_get_financials calls when the question is "what do this company's financials look like right now". Values use the same frame dedup and tag priority as secedgar_get_financials, so the two agree for any concept they both cover. Duration concepts (income statement, cash flow, per-share) report their latest full year and latest single quarter; balance-sheet and entity-info concepts report their latest point-in-time value, since that is the only form they are filed in. A concept the filer does not report is listed under gaps with the XBRL tags that were tried — never zero-filled or interpolated. Use secedgar_get_financials for a full time series of one concept, and secedgar_compare_companies to put several companies side by side.

Search supported XBRL financial concepts by keyword, statement group, or taxonomy. Use before secedgar_get_financials or secedgar_fetch_frames to discover the right friendly name, or pass a raw XBRL tag (e.g., "NetIncomeLoss") to reverse-lookup which friendly names map to it. Empty search with no filters returns the full catalog.

Search EDGAR filings since 1993. Full-text search covers 2001-present (the EFTS index floor); pre-2001 date ranges (to 1993) are served from the archives by form and entity/date. Pre-2001 free text needs entity scope (ticker:/cik:) — with it, the tool reads the entity's matching filings and matches the terms locally, which costs a few seconds (SEC's request rate caps the scan at roughly 5s for the 50-document maximum). A range crossing 2001-01-01 is split at the boundary and the two eras merged, each row tagged with its source. Supports exact phrases, boolean operators, wildcards, and entity targeting (ticker:AAPL or cik:320193 in query). When the match set outruns the inline list it is also staged as df_<id> — inspect it with secedgar_dataframe_describe, then analyze it with secedgar_dataframe_query.