Edgar MCP Service

🏛️ Edgar MCP Service

Model Context Protocol (MCP) Server for SEC EDGAR Database
Deep financial document analysis and content extraction service

🚀 Quick Deploy to Railway

One-Click Deployment:

Fork this repository to your GitHub account
Connect to Railway: Go to Railway → New Project → Deploy from GitHub repo
Set environment variable: SEC_API_USER_AGENT="Your Company/1.0 (your-email@example.com)"
Get your service URL from Railway dashboard
Done! Your MCP service is live

🎯 What This Service Provides

🔍 Universal Company Search

Find ANY public company by name, ticker, or partial match
Works with Apple, Netflix, small caps, recent IPOs, etc.
No hardcoded company lists - truly universal

📄 Deep Document Analysis

Business descriptions from 10-K Item 1
Risk factors from 10-K Item 1A
Financial statements with structured data
Management discussion (MD&A) extraction
Full-text search within any SEC filing

🔗 Advanced Filing Search

Date range filtering: "filings between Jan-Mar 2024"
Form type filtering: 10-K, 10-Q, 8-K, etc.
Content search: "documents mentioning revenue recognition"
Direct SEC EDGAR links for all results

📡 API Endpoints

Company Search

GET /search/company?q=Netflix

Response:

{
  "found": true,
  "cik": "0001065280",
  "name": "NETFLIX INC",
  "ticker": "NFLX",
  "confidence": 1.0
}

Advanced Filing Search

POST /search/filings
{
  "company": "Apple",
  "form_types": ["10-K", "10-Q"],
  "date_from": "2024-01-01",
  "content_search": "artificial intelligence",
  "limit": 10
}

Content Extraction

POST /extract/business-description
{
  "cik": "0000320193",
  "form_type": "10-K"
}

🏗️ Architecture

This MCP service is designed to work with AI query engines:

User Query → AI Engine → Edgar MCP → SEC Database
              ↓
    "Netflix's risk factors" → Company Resolution → Deep Content → Structured Response

Integration Example:

// In your AI application
const edgarMCP = 'https://your-service.up.railway.app';

// 1. Resolve company
const company = await fetch(`${edgarMCP}/search/company?q=Netflix`);

// 2. Get content
const riskFactors = await fetch(`${edgarMCP}/extract/risk-factors`, {
  method: 'POST',
  body: JSON.stringify({ cik: company.cik })
});

// 3. Use in AI analysis
const analysis = await openai.chat.completions.create({
  messages: [{ role: 'user', content: `Analyze these risk factors: ${riskFactors}` }]
});

🛠️ Manual Deployment

Prerequisites

Python 3.11+
Railway account
SEC compliance: proper User-Agent string

Local Development

git clone <this-repo>
cd edgar-mcp-service
chmod +x start.sh
./start.sh

Service runs at http://localhost:8001

Deploy to Railway

railway login
railway init
railway variables set SEC_API_USER_AGENT="Your Company/1.0 (email@example.com)"
railway up

📋 Environment Variables

Variable	Required	Description	Example
`SEC_API_USER_AGENT`	✅	SEC API compliance identifier	`"Crowe/EDGAR Query Engine 1.0 (brett.vantil@crowe.com)"`
`PORT`	⚪	Service port (auto-set by Railway)	`8001`

🔒 SEC Compliance

This service is fully compliant with SEC EDGAR API requirements:

✅ Proper User-Agent identification
✅ Rate limiting respected
✅ Official SEC data sources only
✅ No data caching (always fresh)

🧪 Test Your Deployment

# Health check
curl https://your-service.up.railway.app/health

# Find any company
curl "https://your-service.up.railway.app/search/company?q=Tesla"

# Get business description
curl -X POST "https://your-service.up.railway.app/extract/business-description" \
  -H "Content-Type: application/json" \
  -d '{"cik": "0001318605", "form_type": "10-K"}'

📞 Support

This MCP service enables powerful financial analysis applications by providing:

🎯 Universal access to any SEC-registered company
📊 Deep content extraction beyond basic metadata
🔍 Advanced search capabilities across all filings
🤖 AI-ready responses for natural language processing

Perfect for building financial analysis tools, compliance monitoring, and investment research platforms.

Powered by EdgarTools 📈

This server cannot be installed

security - not tested

license - not found

quality - not tested

How are these scores calculated?

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

Enables deep analysis of SEC EDGAR filings through universal company search, document content extraction, and advanced filing search capabilities. Provides AI-ready access to business descriptions, risk factors, financial statements, and full-text search across any public company's SEC documents.

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