EdgarTools

io.github.dgunning由 GitHub 帳號 dgunning 發布v5.62.1更新於 Oct 24, 2026

Open-source SEC EDGAR toolkit — 13 tools, 7 prompts, every filing type. No API key required.

發布方自己的服務:edgar.tools SEC Intelligence

概覽

AI 產生的概覽

本機 MCP 伺服器,把 SEC EDGAR 申報文件轉為結構化資料:全文檢索、財務報表、內部人交易、13F 與基金持股。

可以做什麼
  • 檢索申報文件內文,並依表單類型、項目或日期區間篩選,也可用 accession 編號、CIK 或股票代號找到文件
  • 取得跨年度、季度及滾動十二個月的標準損益表、資產負債表和現金流量表
  • 讀取 10-K、10-Q 的章節文字,或把整份文件轉成 markdown 供檢索流程使用
  • 擷取 13F 機構持股、Form 4 內部人交易、N-PORT 基金投資組合和 8-K 項目,輸出為結構化物件與表格
適用情境
適合需要回答上市公司向 SEC 申報了什麼、跨公司比較已揭露財務數據,或追蹤內部人交易與機構持股的情境,不必自行撰寫解析程式。
執行需求
透過 uvx 從含 ai 擴充的 edgartools 套件在本機執行(或 pip 安裝後執行 python -m edgar.ai);需要 Python 3.11+ 以及 uv 或 pip。必須設定環境變數 EDGAR_IDENTITY,內容為姓名與聯絡信箱,用於向 SEC 表明身分。需要連線至 SEC EDGAR;不需 API 金鑰或註冊。
安裝前請注意
EDGAR_IDENTITY 會隨每次請求傳送給 SEC,請使用願意公開的真實聯絡信箱。此伺服器只讀取公開文件,但須遵守 SEC 每秒 10 次請求的公平存取限制。不要同時掛載此本機伺服器與託管的 edgar.tools 連接器,兩者功能重疊,會分散助理的路由。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 EdgarTools,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。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

[EdgarTools logo]

EdgarTools — Python Library for SEC EDGAR Filings


[PyPI - Version] [Python versions] [Build status] [Monthly downloads]

EdgarTools is a Python library for SEC EDGAR filings as structured data: financial statements, insider trades, fund holdings, proxy statements and dozens of other filing types, through one consistent Python API. SEC publishes every filing since 1994 for free, and almost none of it is ready to use; EdgarTools turns a filing into a typed Python object. Free and open source, MIT-licensed.

Docs · Cheat sheet · Agents: Skill · MCP server · Hosted: edgar.tools

[EdgarTools SEC filing data extraction demo]

Quick Start

1. Install. The package is edgartools; the module you import is edgar. Python 3.11+.

bash
uv add edgartools        # or: pip install edgartools

2. Identify yourself to the SEC. EDGAR requires a contact email on every request. There is no key, signup or rate-limit tier.

python
from edgar import Company, set_identity
set_identity("[email protected]")

3. Get data.

python
# Five fiscal years of standardized income statement, from XBRLCompany("NVDA").income_statement(periods=5)#> Total Revenue $215.9B $130.5B $60.9B

Why not just call SEC's APIs?

data.sec.gov gives you JSON facts and filing indexes. Everything past that is your code. EdgarTools does that part:

  • Section text and markdown. Item 1A, Item 7 or any Item of a 10-K or 10-Q as text, and whole filings as markdown for RAG. Raw HTML is where hand-rolled parsers break.
  • Parsed forms, not XML. 13F holdings, Form 4 transactions, N-PORT portfolios and 8-K items as typed objects and DataFrames.
  • Statements that line up. Rows standardized across filers, so "Total Revenue" means the same thing for a bank and a chipmaker, plus discrete quarters (Q4 derived from the 10-K) and trailing twelve months.
  • Search and plumbing. Full-text search over filing content, the live filing feed, rate limiting, caching and offline storage.

It runs in your own process, MIT-licensed, with no API key and no vendor quota; SEC's fair-access limit of 10 requests a second still applies, and EdgarTools keeps to it.

What you can do

Full-text search across SEC filings

Search the text of every filing since 2001, not just form types and dates.

python
from edgar import search_filings
# Every 10-K filed since 2025 that mentions tariffsresults = search_filings("tariff", forms="10-K", start_date="2025-01-01")hit = results[0]hit.accession_number, hit.form, hit.filed, hit.company  # a hit's fields; filed is the filing datehit.get_filing()  # the Filing behind a hit, ready for .obj() or .markdown()
# Structured: 8-Ks that reported a cybersecurity incident (Item 1.05) in 2025search_filings(forms="8-K", items="1.05", start_date="2025-01-01", end_date="2025-12-31")#> 19 total

Full-text search guide →

Financial statements over several years

python
Company("MSFT").income_statement(periods=10)  # also .balance_sheet() and .cash_flow_statement()

Financial Statements guide →

One metric across companies

Pick rows by their standardized label, never by position: the first row of an income statement is not always total revenue.

python
import pandas as pd
revenue = {    ticker: Company(ticker).income_statement(periods=3, as_dataframe=True)            .set_index("label").filter(like="FY").loc["Total Revenue"] / 1e9    for ticker in ["JPM", "PFE", "CAT"]}pd.DataFrame(revenue).round(1)  # $ billions#> FY 2025 182.4 62.6 67.6

Quarterly figures and trailing twelve months

python
nvda = Company("NVDA")nvda.get_ttm_revenue()                                 # the last four quarters, summednvda.income_statement(period="quarterly", periods=8)   # discrete quarters; Q4 is derived from the 10-K

Sections and markdown for RAG

python
filing = Company("NVDA").latest("10-K")filing.markdown()          # the whole filing as markdown
tenk = filing.obj()tenk.risk_factors          # Item 1A as texttenk["Item 1C"]            # any Item by number

Sections guide →

Find filings, by anything

python
from edgar import find, get_current_filings, get_filings
get_filings(2025, 4, form="10-K")   # every 10-K filed in Q4 2025get_current_filings()               # the live feed, as SEC posts itfind("0000320193-25-000079")        # an accession number, CIK or ticker

Finding filings guide →

[find() resolving a ticker, a CIK and an accession number]

[get_current_filings() showing the live SEC filing feed]

13F institutional holdings

python
thirteenf = Company("BRK.A").get_filings(form="13F-HR").latest().obj()thirteenf.holdings  # one row per security: Issuer, Cusip, Ticker, SharesPrnAmount, Value, ...

Institutional Holdings guide →

[Berkshire Hathaway's latest 13F holdings]

Insider trades from Form 4

python
form4 = Company("TSLA").get_filings(form="4").latest().obj()form4.to_dataframe()  # buys, sells, grants and exercises

Insider Trades guide →

[Tesla's latest Form 4 parsed into a structured object]

Fund holdings from N-PORT

python
from edgar import Fund
Fund("VOO").get_portfolio()  # the latest N-PORT holdings as a DataFrame

Fund Portfolios guide →

8-K events and earnings releases

python
eightk = find("0001045810-26-000073").obj()  # NVIDIA, 2026-08-26eightk.items      # ['Item 2.02', 'Item 9.01']eightk.earnings   # the EX-99.1 press release tables, parsed

Current Events guide →

Library or hosted?

EdgarTools is this library: free, MIT-licensed, running in your own Python process. edgar.tools is the hosted platform built on it: the same parsing, kept running and current, with every answer cited to its filing. You are not paying for the parsing; you are paying for it to be run and answerable. No feature is ever removed from the library to sell the platform.

If you want to…Use
Build something that runs: pipelines, backfills, backtests, model corpora, notebooks, custom joins, anything repeated across hundreds of names or run inside your own networkThe library
Ask, not build: what the companies you cover filed and what changed since last time, who sold, who holds it, one person across every company they touch, screens across a universe, alerts, cited answers to forward or share with a team. From a browser, a phone, Excel, Claude or ChatGPT, or an agent that cannot run Pythonedgar.tools. Free account to start
Own a maintained dataset (insider trades, 13F, BDC portfolios, material events), every row traceable to its filing, without running the pipelineedgar.tools data licensing
Fetch one known filing or one JSON document, once, from a scriptNeither: call EDGAR directly

Both have an MCP server: the library's runs locally (see AI Integration below), and edgar.tools' is hosted at app.edgar.tools/mcp. Attach one per client, not both: they overlap and split your assistant's routing.

AI integration

EdgarTools ships an agent skill and a local MCP server, both in the ai extra. For an assistant that cannot run Python, use the hosted connector from the section above instead.

bash
pip install "edgartools[ai]"python -c "from edgar.ai import install_skill; install_skill()"  # the skill, for Claude Code and Claude Desktop

The MCP server works with any MCP client. For Claude Desktop, add it to claude_desktop_config.json:

json
{  "mcpServers": {    "edgartools": {      "command": "uvx",      "args": ["--from", "edgartools[ai]", "edgartools-mcp"],      "env": {        "EDGAR_IDENTITY": "Your Name [email protected]"      }    }  }}

uvx needs uv; without it, pip install "edgartools[ai]" and run python -m edgar.ai. Setup for other clients: MCP server guide · Skill guide.

Support the project

The SEC changes filing formats and ships a new XBRL taxonomy every year. Sponsorship is what keeps the parsers current and pays for new ones as new disclosures appear.

  • GitHub Sponsors: monthly or one-time. Companies can sponsor on their existing GitHub bill.
  • Buy Me a Coffee: a one-time thank-you.
  • Consulting: help from the library's author with SEC data pipelines and financial AI built on it.

[Sponsor on GitHub]    [Buy Me A Coffee]

Docs, help and contributing

EdgarTools is distributed under the MIT License.

來源:README.md,提交 018156a

工具

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SourceWeft 曾在隔離沙箱中以無憑證方式啟動該軟體包一次,以列出其工具,但未能完成:伺服器未能啟動。

版本歷史

5
  1. v5.62.1最新Oct 23, 2026
  2. v5.62.0Oct 11, 2026
  3. v5.61.1Oct 7, 2026
  4. v5.61.0Oct 6, 2026
  5. v5.21.1Sep 16, 2026

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