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  3. EdgarTools
EdgarTools logo
Health: ActiveRecent health check succeeded.Last checked 9/7/2026, 7:35:45 PM

EdgarTools

User RatingsBe the first to rate and review this MCP server! Enrichment pendingWe haven’t run our AI enrichment pass on this listing yet, so the overview, use cases, and FAQ below may be sparse or missing. We work through the catalog over time β€” check back soon.
View Repository2.7k GitHub StarsTotal stargazers on GitHub for the source repository (2,679 stars).Visit Website

Open-source SEC EDGAR toolkit β€” 11 tools, 7 prompts, every filing type. No API key required.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag β€” we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "edgartools": {
      "command": "uvx",
      "args": [
        "--from"
      ]
    }
  }
}

πŸ’‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing AlternativesπŸ’» More in Developer Tools

Documentation Overview

EdgarTools logo

EdgarTools β€” Python Library for SEC EDGAR Filings


PyPI - Version GitHub Workflow Status Regression Tests CodeFactor GitHub Documentation Pepy Total Downloads Pepy Monthly Downloads GitHub stars

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 β€” in a few lines of code. Free and open source.

EdgarTools SEC filing data extraction demo

Why EdgarTools?

SEC EDGAR has every filing back to 1994, free β€” 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.

server.ts
# Apple's latest income statement β€” rendered, standardized, done
from edgar import Company
Company("AAPL").get_financials().income_statement()
Financial Statements
Financial Statements
Income, balance sheet, cash flow in one call
XBRL-standardized for cross-company comparison
Every Filing Type
Every Filing Type
13F holdings, Form 4 insiders, 8-K events, funds, proxies
Typed objects + pandas DataFrames for 20+ forms
Built for Pipelines & AI
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 β€” its data ready as pandas DataFrames and clean text.

How EdgarTools turns any SEC filing into a typed Python object

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

Terminal
pip install edgartools

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

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

3. Get data β€” every filing is now a few lines away:

python
# 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()

Apple SEC Form 4 insider transactions parsed into a structured Python object

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

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

Financial Statements guide β†’

Insider trading from SEC Form 4

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

Insider Trades guide β†’

13F institutional holdings & hedge fund portfolios

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

Institutional Holdings guide β†’

8-K current reports & corporate events

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

Current Events guide β†’

XBRL financial data across companies

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

XBRL Deep Dive β†’

Key Features

Financial data

  • Income, balance sheet, cash flow β€” 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 β†’ 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 β†’

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 β€” the difference is how you work with the data, and what it costs you.

EdgarToolssec-api
CostFree, MIT$49+/mo
Data formatTyped Python objects β†’ DataFramesJSON you parse yourself
Where it runsIn your process β€” no key, no quotas, no vendor lock-inHosted API β€” key + rate tiers
Filing coverage20+ typed forms (10-K, 8-K, 13F, N-PORT, proxy…)15+ structured endpoints
AI / MCP Built in
Open source Inspect, fork, self-host Proprietary

Bottom line: in Python, EdgarTools gives you typed objects, AI-native output, and the full SEC corpus β€” 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 β€” 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 β€” and without the black box of a closed API.

Read the full README β†’View source on GitHub β†’

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Reviews

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Frequently Asked Questions about EdgarTools

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "edgartools": { "command": "npx", "args": ["-y", "EdgarTools"] } }

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Technical Specs & Signals

CategoryπŸ’»Developer Tools
More technical detailsExpand β–Ύ
TransportSTDIO
RuntimePython
Last updatedSep 7, 2026
Views0
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars2,679
GitHub Star CountTotal stargazers on GitHub representing community popularity (2,679 stars).
44Quality signal: Fair Β· 44/100How this signal is calculated β–Ύ
Server availabilityNot measured

Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools16/30
Adoption & activity7/15
Community engagement0/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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