edgar.tools SEC Intelligence

SEC filing intelligence — insider sentiment, material events, financial ratios, disclosure search.

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README

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<h1 align="center">EdgarTools - Python Library for SEC EDGAR Filings</h1>
<h3 align="center">The simplest, most complete Python library for SEC EDGAR data</h3>

<p align="center">
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<p align="center">
  <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/badges/badge-ai-native.svg" alt="AI Native">
  <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/badges/badge-10x-faster.svg" alt="10x Faster">
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  <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/badges/badge-financial-data.svg" alt="Financial Data">
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<p align="center">
  <b>Get financial statements, insider trades, fund holdings, and 20+ other filing types as structured Python objects — in a few lines of code. Free and open source.</b>
</p>

**EdgarTools** is a Python library for accessing SEC EDGAR filings as structured data. Parse financial statements, insider trades, fund holdings, proxy statements, and dozens of other filing types with a consistent Python API.

![EdgarTools SEC filing data extraction demo](https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/edgartools-demo.gif)

<p align="center">
  <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/dividers/divider-hexagons.svg" alt="">
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## Why EdgarTools?

EdgarTools turns SEC filings into Python objects. Every supported form type gives you structured data — not raw HTML, not XML, not JSON dumps. Actual Python objects with properties, methods, and DataFrames.

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  <td align="center" width="33%">
    <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/icons/icon-speed.svg" width="80" alt="Fast"><br>
    <b>Fast</b><br>
    Optimized with lxml & PyArrow<br>
    Smart caching, rate-limit aware
  </td>
  <td align="center" width="33%">
    <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/icons/icon-ai.svg" width="80" alt="AI Ready"><br>
    <b>AI Ready</b><br>
    Built-in MCP server for Claude<br>
    LLM-optimized text extraction
  </td>
  <td align="center" width="33%">
    <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/icons/icon-quality.svg" width="80" alt="Well Tested"><br>
    <b>Well Tested</b><br>
    1000+ verification tests<br>
    Type hints throughout
  </td>
</tr>
<tr>
  <td align="center" width="33%">
    <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/icons/icon-xbrl.svg" width="80" alt="XBRL Support"><br>
    <b>XBRL Native</b><br>
    Full XBRL standardization<br>
    Cross-company comparisons
  </td>
  <td align="center" width="33%">
    <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/icons/icon-data.svg" width="80" alt="20+ Filing Types"><br>
    <b>20+ Filing Types</b><br>
    Typed objects for every form<br>
    Pandas-ready DataFrames
  </td>
  <td align="center" width="33%">
    <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/icons/icon-community.svg" width="80" alt="Open Source"><br>
    <b>Open Source</b><br>
    MIT license, free forever<br>
    No API keys, no rate limits
  </td>
</tr>
</table>

<p align="center">
  <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/dividers/divider-hexagons.svg" alt="">
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## How It Works

<