EdgarTools — Python Library for SEC EDGAR Filings

EdgarTools is a Python library for accessing SEC EDGAR filings as structured data. Parse financial statements, insider trades, fund holdings, proxy statements, and 20+ other filing types with a consistent Python API — in a few lines of code. Free and open source.

Why EdgarTools?

SEC EDGAR has every filing back to 1994, free — and almost none of it is ready to use. EdgarTools turns any filing into a typed Python object, so a 10-K's revenue is one line instead of an afternoon of XBRL parsing.

# Apple's latest income statement — rendered, standardized, done
from edgar import Company
Company("AAPL").get_financials().income_statement()

Income, balance sheet, cash flow in one call XBRL-standardized for cross-company comparison Every Filing Type 13F holdings, Form 4 insiders, 8-K events, funds, proxies Typed objects + pandas DataFrames for 20+ forms Built for Pipelines & AI Rate-limit aware, smart caching, enterprise mirrors Built-in MCP server + LLM-ready text for RAG

How It Works

Everything starts with a Company or a Filing. Call .obj() and you get a typed object built for that form — its data ready as pandas DataFrames and clean text.

The same typed output that reads cleanly in a notebook drops straight into a pipeline: DataFrames for your warehouse, LLM-ready text and an MCP server for your AI stack, rate-limit and enterprise-mirror aware for scale.

Quick Start

1. Install

pip install edgartools

2. Identify yourself to the SEC — EDGAR requires an email with every request. No key, no signup, no rate-limit tier; set it once:

from edgar import *
set_identity("your.name@example.com")

3. Get data — every filing is now a few lines away:

# Standardized financial statements, straight from XBRL
Company("AAPL").get_financials().income_statement()

# The latest insider Form 4 as a structured object
Company("AAPL").get_filings(form="4").latest().obj()

Next: explore the Use Cases below, or dive into the documentation and Quick Guide.

Use Cases

Financial statements from 10-K and 10-Q filings

financials = Company("MSFT").get_financials()
financials.balance_sheet()     # all line items
financials.income_statement()  # revenue, net income, EPS

Financial Statements guide →

Insider trading from SEC Form 4

form4 = Company("TSLA").get_filings(form="4").latest().obj()
form4.to_dataframe()  # insider buy/sell transactions

Insider Trades guide →

13F institutional holdings & hedge fund portfolios

thirteenf = get_filings(form="13F-HR").latest().obj()
thirteenf.holdings  # every portfolio position as a DataFrame

Institutional Holdings guide →

8-K current reports & corporate events

eightk = get_filings(form="8-K").latest().obj()
eightk.items  # reported event items

Current Events guide →

XBRL financial data across companies

facts = Company("AAPL").get_facts()
facts.query().by_concept("Revenue").to_dataframe()  # revenue history as a DataFrame

XBRL Deep Dive →

Key Features

Financial data

• Income, balance sheet, cash flow — XBRL-standardized for cross-company comparison
• Individual line items, dimensional data, multi-period comparatives
• Company Facts API: time-series for any concept across years

Funds & ownership

• 13F holdings, N-PORT, N-MFP, N-CSR/N-CEN fund reports
• Form 3/4/5 insider transactions; Schedule 13D/G ownership
• Position tracking over time

Filings & text

• Typed objects for 20+ forms; complete history since 1994
• Section extraction (Risk Factors, MD&A), EX-21 subsidiaries, auditor info
• HTML → clean text + markdown for RAG; full-text search
• Ticker/CIK lookup, industry & exchange filtering

Built for production

• Configurable rate limiting + enterprise/academic mirrors
• Smart caching, type hints throughout, 1000+ tests
• Enterprise configuration →

EdgarTools supports all SEC form types including 10-K annual reports, 10-Q quarterly filings, 8-K current reports, 13F institutional holdings, Form 4 insider transactions, proxy statements (DEF 14A), S-1 registration statements, N-CSR fund reports, N-MFP money market data, N-PORT fund portfolios, Schedule 13D/G ownership, Form D offerings, Form C crowdfunding, and Form 144 restricted stock. Parse XBRL financial data, extract text sections, and convert filings to pandas DataFrames.

Comparison with Alternatives

EdgarTools is a Python library that talks directly to SEC EDGAR. sec-api is the best-known hosted API that returns JSON. Both parse filings — the difference is how you work with the data, and what it costs you.

Bottom line: in Python, EdgarTools gives you typed objects, AI-native output, and the full SEC corpus — free, open, and inspectable, with no keys or bills. pip install edgartools and you're querying filings in two lines.

Library or hosted?

EdgarTools is the open-source library — SEC-filing primitives you compose in your own code, free and self-run.

edgar.tools is the hosted platform built on that same open engine: the full SEC corpus as a managed service, so your team gets the data without running the pipeline — and without the black box of a closed API.

Reach for the library when you want control in your own stack; reach for edgar.tools when you'd rather not operate it yourself.

AI Integration

Use EdgarTools with Claude Code & Claude Desktop

EdgarTools includes an MCP server and AI skills for Claude Desktop and Claude Code. Ask questions in natural language and get answers backed by real SEC data.

• "Compare Apple and Microsoft's revenue growth rates over the past 3 years"
• "Which Tesla executives sold more than $1 million in stock in the past 6 months?"

Option 1: AI Skills (Recommended)

Install the EdgarTools skill for Claude Code or Claude Desktop:

pip install "edgartools[ai]"
python -c "from edgar.ai import install_skill; install_skill()"

This adds SEC analysis capabilities to Claude, including 3,450+ lines of API documentation, code examples, and form type reference.

Option 2: MCP Server

Run EdgarTools as an MCP server for any AI client -- Claude Desktop, Cline, or your own containerized deployment.

Add to Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json):

{
  "mcpServers": {
    "edgartools": {
      "command": "uvx",
      "args": ["--from", "edgartools[ai]", "edgartools-mcp"],
      "env": {
        "EDGAR_IDENTITY": "Your Name your.email@example.com"
      }
    }
  }
}