FilingFirehose

com.filingfirehose由 filingfirehose.com 發布官方發布者v0.1.0更新於 Oct 24, 2026

SEC EDGAR filings parsed: 8-K body-text classification, 13D activist tagging, S-3 ATM detection.

已驗證Streamable HTTP可網頁執行金融資料與分析

概覽

AI 產生的概覽

遠端 MCP 伺服器，用來檢索近期 SEC EDGAR 申報文件——8-K、維權投資人 13D/13G 與 ATM 發行——並依 accession 編號取得單一文件。

可以做什麼
檢索過去 72 小時內的 8-K 申報，可依資安事件、高階主管離職、重大協議等項目代碼篩選，並可只顯示內文與申報項目不符的疑似隱匿事件。檢索近期的 Schedule 13D/13G 申報，可依維權投資人名稱或最低揭露持股比例篩選。檢索從 S-3 與 424B5 文件擷取的近期按市價（ATM）股權發行，可依銷售代理或發行規模篩選。依 SEC accession 編號取得不限時間的單一申報文件。
適用情境
適合需要追蹤近期公司事件的研究或監控流程，例如資安事件、高階主管異動、維權持股或股權發行，不必直接查詢 EDGAR；也適合依引用中的 accession 編號取得已解析的申報細節。
執行需求
遠端 streamable HTTP 端點；未宣告本機執行環境、環境變數或請求標頭。README 說明免費公開層涵蓋最近 72 小時且不需 API 金鑰，完整歷史檔案則需要 API 金鑰。
安裝前請注意
免費層僅限最近 72 小時，存取更早的檔案需向提供者申請 API 金鑰。隱匿事件與 ATM 標記屬於解析器的啟發式判斷，並非權威分類，採取行動前應核對原始申報文件。查詢內容與 accession 編號會傳送到提供者的服務。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 FilingFirehose，將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Web executable，透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式，或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南，先向你展示發布者、端點和登入方式，經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/com.filingfirehose%2Ffirehose/install.md，並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前，先告訴我它的發布者、端點和登入方式，等我確認。不要把 API 金鑰寫進命令或我會提交的檔案；問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。

{
  "mcpServers": {
    "filingfirehose": {
      "type": "http",
      "url": "https://filingfirehose.com/mcp"
    }
  }
}

README

filing-firehose

Python client for the FilingFirehose SEC EDGAR API — body-text-parsed 8-Ks (with buried-event detection), activist-tagged Schedule 13D/G filings, and ATM offerings extracted from S-3 / 424B5 prospectus supplements.

Install

pip install filing-firehose

Quick start

The free public tier returns the last 72 hours of filings — no API key required:

python
from filing_firehose import FilingFirehose
ff = FilingFirehose()
# Recent 8-Ks where the body language flags items the filer didn't reportburied = ff.recent_8k(suspected_buried_only=True, limit=10)for f in buried:    print(f"{f.company_name}: filer reported {f.filer_reported_items}, "          f"body suggests {f.suspected_buried_events}")
# Recent activist 13D / 13G filingsfor f in ff.recent_13d(activist="Saba"):    print(f"{f.company_name} — {f.percent_of_class}% by {f.activist_filers}")
# Recent ATM offerings with shelf size > $50Mfor f in ff.recent_atm(min_shelf_million_usd=50):    print(f"{f.company_name}: ${f.shelf_size_million_usd:.1f}M via {f.sales_agents}")

For the full historical archive, get an API key at filingfirehose.com:

python
ff = FilingFirehose(api_key="ff_live_...")
# Search the entire archive for cyber eventsfor f in ff.search_8k(items="1.05", since="2026-01-01"):    print(f.company_name, f.filed_at)

Async

python
import asynciofrom filing_firehose import AsyncFilingFirehose
async def main():    async with AsyncFilingFirehose() as ff:        filings = await ff.recent_8k(items="1.05,5.02")        for f in filings:            print(f.company_name, f.detected_items)
asyncio.run(main())

Why this client

The wedge: most SEC filings APIs trust the filer-reported item codes on 8-K filings. We body-text-classify every filing and surface a suspected_buried_events field flagging when the body language doesn't match the filer's claimed item codes. From a 21-day analysis of 4,251 8-Ks, 7.3% of Item 8.01 filings contain language suggesting a more specific item should have been used — including buried cyber incidents (1.05), officer departures (5.02), and material agreements (1.01).

License

MIT.

來源：README.md，提交 16fe79e

工具

4

search_8k_filings

Search recent SEC 8-K filings (current report) from the past 72 hours. Args: items: Comma-separated 8-K item codes to filter on. Examples: '1.05' (cybersecurity), '5.02' (officer departure), '8.01' (other events), '1.01' (material agreement). Leave None for all 8-Ks. suspected_buried_only: If True, return only filings where our body-text classifier flagged a suspected misclassification — i.e. cyber language under Item 8.01 that should have been 1.05, officer-departure language under 8.01 that should have been 5.02. limit: Max results (1-50, default 25). Returns: JSON-formatted list of filings. Each includes: accession_number, company_name, filed_at, filer_reported_items, detected_items, discrepancy_items (in body but not reported), and suspected_buried_events (map of reported→suspected).

輸入參數itemslimitsuspected_buried_only

search_13d_filings

Search recent SEC Schedule 13D / 13G filings from the past 72 hours. Args: activist: Filter to filings tagged with this activist filer name. Substring match, case-insensitive. Examples: 'Saba', 'Starboard', 'Icahn', 'Elliott', 'Pershing'. min_percent: Minimum percent of class disclosed. include_amendments: Include 13D/A and 13G/A amendments. Default True. include_passive_13g: Include passive Schedule 13G filings. Default False (only active 13D / 13D/A returned). limit: Max results (1-50, default 25). Returns: JSON list of filings with cusip, percent_of_class, aggregate_amount, activist_filers, and an Item 4 purpose excerpt.

輸入參數limitactivistmin_percentinclude_amendmentsinclude_passive_13g

search_atm_offerings

Search recent SEC at-the-market (ATM) equity offerings from the past 72 hours. Pulls from S-3 / 424B5 family filings where our parser flagged ATM-offering indicators in the body language. Args: sales_agent: Filter by sales agent name (substring, case-insensitive). Examples: 'Cantor Fitzgerald', 'Jefferies', 'Roth Capital', 'H.C. Wainwright'. min_shelf_million_usd: Minimum shelf size in millions USD. limit: Max results (1-50, default 25). Returns: JSON list with shelf_size_usd, is_atm, sales_agents, use_of_proceeds_excerpt.

輸入參數limitsales_agentmin_shelf_million_usd

get_filing

Fetch one filing by SEC accession number, regardless of recency. Useful when an agent has an accession number from a citation or earlier tool call and needs the parsed details. Args: accession_number: SEC accession in 'XXXXXXXXXX-YY-NNNNNN' format. Returns: JSON for the filing if found in our archive, or {"found": false}.

輸入參數accession_number必填

版本歷史

1
  1. v0.1.0最新Sep 16, 2026

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