Add it to Claude Code
claude mcp add -e "EDGAR_IDENTITY=${EDGAR_IDENTITY}" edgartools-mcp -- python -m edgar.mcpEDGAR_IDENTITYMake your agent remember this setup
edgartools-mcp's config, env vars, and the gotchas you hit — recalled in every future Claude Code, Cursor, and Codex session.
npx conare@latestFree · one command · indexes the sessions already on disk. Set up in the browser instead →
What it does
- Download and parse SEC EDGAR filings including 10-K, 10-Q, and 8-K reports
- Standardized XBRL financial statement extraction
- Access to insider trading data via Form 4 filings
- LLM-optimized text extraction for financial analysis
- Pandas-ready data output for financial modeling
Tools 3
get_company_filingsRetrieve SEC filings for a specific company ticker.get_financialsExtract financial statements like balance sheets and income statements.get_insider_tradingAccess insider trading data from Form 4 filings.Environment Variables
EDGAR_IDENTITYrequiredRequired by SEC regulations to identify your application (e.g., [email protected])Try it
Original README from sareegpt/edgartools-mcp
<b>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.</b>
<sub>Built with AI-assisted development • 3-10x faster velocity • Support this project</sub>
EdgarTools is a Python library for downloading and analyzing SEC EDGAR filings. Extract 10-K, 10-Q, 8-K reports, parse XBRL financial statements, and access insider trading data (Form 4) with a simple Python API. Free and open-source.
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.
<table align="center"> <tr> <td align="center" width="33%"><b>Lightning Fast</b>
10-30x faster than alternatives
Optimized with lxml & PyArrow
<b>AI Native</b>
Built-in MCP server for Claude
LLM-optimized text extraction
<b>Production Quality</b>
1000+ tests, type hints
Battle-tested by analysts
<b>XBRL Native</b>
Full XBRL standardization
Cross-company comparisons
<b>Rich Data Objects</b>
Smart parsing for every form
Pandas-ready DataFrames
<b>Open Source</b>
MIT license, community-driven
Transparent & auditable
How It Works
# Install the SEC EDGAR Python library
pip install edgartools
# Set your identity (required by SEC regulations)
from edgar import *
set_identity("[email protected]")
# Get SEC 10-K, 10-Q filings and XBRL financial statements
balance_sheet = Company("AAPL").get_financials().balance_sheet()
# Access any company's SEC filings
company = Company("MSFT")
# Parse Form 4 insider trading tra