edgartools

The AI Native Python library for SEC EDGAR Data

The only SEC EDGAR library built from the ground up for AI agents and LLMs. Extract financial data in 3 lines of code instead of 100+. Production-ready MCP server included.

_{Built with AI-assisted development • 3-10x faster velocity • Support this project}

Why EdgarTools?

EdgarTools is the fastest, most powerful open-source library for SEC EDGAR data extraction. Built for financial analysts, data scientists, and AI developers who need reliable, production-ready access to SEC filings.

Lightning Fast 10-30x faster than alternatives Optimized with lxml & PyArrow	AI Native Built-in MCP server for Claude LLM-optimized text extraction	Production Quality 1000+ tests, type hints Battle-tested by analysts
XBRL Native Full XBRL standardization Cross-company comparisons	Rich Data Objects Smart parsing for every form Pandas-ready DataFrames	Open Source MIT license, community-driven Transparent & auditable

How It Works

# 1. Install
pip install edgartools

# 2. Set your identity (required by SEC regulations)
from edgar import *
set_identity("[e-mail]")

# 3. Get company financials in 1 line
balance_sheet = Company("AAPL").get_financials().balance_sheet()

# 4. Explore with interactive documentation
company = Company("MSFT")

# 5. Or explore insider transactions
filings = company.get_filings(form="4")
form4_filing = filings[0]
form4 = form4_filing.obj()

Comprehensive SEC Data Access

Financial Statements (XBRL) Balance Sheets, Income Statements, Cash Flows Individual line items via XBRL tags Multi-period comparisons with comparative periods Standardized cross-company data Automatic unit conversion Metadata columns (dimensions, members, units) Complete dimensional data support Fund Holdings (13F) Complete 13F filing history Portfolio composition analysis Position tracking over time Ownership percentages Value calculations Company Dataset & Reference Data Industry and state filtering Company subsets with metadata Standardized industry classifications SEC ticker/CIK lookups Exchange information Insider Transactions Form 3, 4, 5 structured data Transaction history by insider Ownership changes Grant and exercise details Automatic parsing

Filing Intelligence Any form type (10-K, 10-Q, 8-K, S-1, etc.) Complete history since 1994 Smart data objects for each form Automatic HTML to clean text Section extraction (Risk Factors, MD&A) Performance & Reliability 10-30x faster than alternatives Configurable rate limiting (enterprise mirrors supported) Custom SEC data sources (corporate/academic mirrors) Smart caching (30-second fresh filing cache) Robust error handling SSL verification with fail-fast retry Type hints throughout Enterprise configuration → Developer Experience Intuitive, consistent API Pandas DataFrame integration Rich terminal output Comprehensive documentation 1000+ tests

Comparison with Alternatives

Feature	EdgarTools	sec-api (paid)	OpenEDGAR	Manual Scraping
AI/MCP Integration
Cost	Free	$150+/mo	Free	Free
Speed	10-30x baseline	Fast (API)	Slow	Slow
XBRL Support	Full	Partial
Financial Statements	Parsed	Parsed	Basic	DIY
LLM-Ready Output
Type Hints
Rate Limiting	Auto	N/A (API)	Manual	Manual
Open Source	MIT	Proprietary	Apache	N/A

Use EdgarTools with Claude Code & Claude Desktop

EdgarTools provides AI Skills that enable Claude and other AI assistants to perform sophisticated SEC filing analysis. Once configured, you can ask Claude questions like:

• "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?"
• "Find all technology companies that filed proxy statements with executive compensation changes"

Claude will write the Python code, execute it, and explain the results - all powered by EdgarTools.

Setup Instructions

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 Claude Code or Claude Desktop:

pip install "edgartools[ai]"
python -m edgar.ai

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

{
  "mcpServers": {
    "edgartools": {
      "command": "python",
      "args": ["-m", "edgar.ai"],
      "env": {
        "EDGAR_IDENTITY": "Your Name [e-mail]"
      }
    }
  }
}

See AI Integration Guide for complete documentation.

Support AI Powered Development

I build and maintain EdgarTools solo using AI-assisted development. Your support directly funds the Claude Max subscription that makes this extraordinary velocity possible.

The Virtuous Cycle

You Support Buy Me A Coffee contributions fund Claude Max

AI Acceleration Specialized agents deliver 3-10x faster development

Rapid Delivery Features in days instead of weeks 24 releases / 60 days

You Benefit More features, faster fixes, free forever

Real Impact: Last 60 Days

24 Releases 1 every 2.5 days

322 Commits 5.4 per day

3-10x Velocity vs traditional dev

Days Not Weeks for major features

Recent Examples

Feature	Traditional Estimate	With AI	Speedup
XBRL Period Selection	3-4 weeks	5 days	7x faster
MCP Workflow Tools	2-3 weeks	2 days	10x faster
HTML Parsing Rewrite	2 weeks	3 days	4x faster
Standardized Concepts API	2 weeks	2-3 days	5x faster

  

What your support enables:

• Claude Max subscription (AI agents that write, test, and document code)
• Continued 3-10x development velocity (features in days, not weeks)
• Rapid response to SEC format changes and bug reports
• New features based on community needs
• Free access for everyone, forever (no API keys, no rate limits)

Alternative ways to support:

• Star the repo on GitHub
• Report bugs and contribute fixes
• Improve documentation
• Answer questions in Discussions
• Share EdgarTools with colleagues

Corporate users: If your organization depends on EdgarTools for SEC compliance or regulatory reporting, GitHub Sponsors offers strategic sponsorship options designed for mission-critical dependencies.

Documentation & Resources

• User Journeys / Examples
• Quick Guide
• Full API Documentation
• EdgarTools Blog

Get Help & Connect

• GitHub Issues - Bug reports and feature requests
• Discussions - Questions and community discussions

Contributing

We welcome contributions from the community! Here's how you can help:

• Code: Fix bugs, add features, improve documentation
• Examples: Share interesting use cases and examples
• Feedback: Report issues or suggest improvements
• Spread the Word: Star the repo, share with colleagues

See our Contributing Guide for details.

EdgarTools is distributed under the MIT License

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