Edgartools MCP Server

edgartools

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

2.6k 4 tools GitHub PyPI

No known CVEs

MIT license

Actively maintained

Last commit 0d ago

Works with most clients

Transport: stdio, sse, http

4 tools · ~104 tok

Grade A · 0.1% of 200K ctx

MCPpedia last refreshed this data 8h ago

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Edgartools MCP Server is an MCP server that open-source SEC EDGAR toolkit — 11 tools, 7 prompts, every filing type. No API key required. Its tool list has not been published yet over stdio, sse and http, requires no API key, and scores 91/100 on MCPpedia's security, maintenance and efficiency rubric.

Finance Data

Step 1

Install in your client

Config is the same across clients — only the file and path differ.

Supported in Claude Desktopstdio, sse, http · Node 18+

Paste into ~/Library/Application Support/Claude/claude_desktop_config.json

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

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Read me

What Edgartools MCP Server does

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.

Test This Server

Run this in your terminal to verify the server starts. Then let us know if it worked — your result helps other developers.

uvx 'edgartools' 2>&1 | head -1 && echo "✓ Server started successfully"

After testing, let us know if it worked:

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Scored, not listed

Why this score

Five weighted categories — click any category to see the underlying evidence.

Score breakdown

91/100across 5 weighted dimensions

How we score →

0255075100

−9

Security

Maintenance

Efficiency

Documentation

Compatibility

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Security

OSV.dev

No known CVEs.

Checked edgartools against OSV.dev.

Inventory

Tools (4)

Click any tool to inspect its schema.

~104 tokens total

Community

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Frequently Asked Questions

Is Edgartools MCP Server safe to use?: Edgartools MCP Server has no known CVEs as of the latest MCPpedia security scan. It does not require authentication, so any local process can connect — keep this in mind in shared environments. Licensed under MIT.
How do I install Edgartools MCP Server?: Edgartools MCP Server supports copy-paste install configs on its MCPpedia page for Claude Desktop, Cursor, and Claude Code. Scroll to the Quick Install section and select your client.
What can Edgartools MCP Server do?: Edgartools MCP Server provides 4 tools: Code, Examples, Feedback, Contributing. See the full tools list on the server page for descriptions and parameters.
What AI clients work with Edgartools MCP Server?: Edgartools MCP Server is compatible with claude-desktop, cursor, claude-code. It uses stdio and sse and http transport.
Is Edgartools MCP Server actively maintained?: Edgartools MCP Server is actively maintained — last commit was 0 days ago. It has 2,604 GitHub stars.

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Community

Discussion

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Has anyone used this with Cursor?How do you handle auth?Any alternatives?

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

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()

Financial Statements
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

Frequently Asked Questions

Is Edgartools MCP Server safe to use?

Edgartools MCP Server has no known CVEs as of the latest MCPpedia security scan. It does not require authentication, so any local process can connect — keep this in mind in shared environments. Licensed under MIT.

How do I install Edgartools MCP Server?

Edgartools MCP Server supports copy-paste install configs on its MCPpedia page for Claude Desktop, Cursor, and Claude Code. Scroll to the Quick Install section and select your client.

What can Edgartools MCP Server do?

Edgartools MCP Server provides 4 tools: Code, Examples, Feedback, Contributing. See the full tools list on the server page for descriptions and parameters.

What AI clients work with Edgartools MCP Server?

Edgartools MCP Server is compatible with claude-desktop, cursor, claude-code. It uses stdio and sse and http transport.

Is Edgartools MCP Server actively maintained?

Edgartools MCP Server is actively maintained — last commit was 0 days ago. It has 2,604 GitHub stars.

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?

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

Financial Statements
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.

... View full README on GitHub