sec-mcp by openpharma-org - MCP Server

Unofficial SEC EDGAR MCP Server

A Model Context Protocol (MCP) server that provides comprehensive access to the U.S. Securities and Exchange Commission's EDGAR (Electronic Data Gathering, Analysis, and Retrieval) system. This server enables AI assistants and applications to search, retrieve, and analyze public company filings, financial statements, and dimensional XBRL data from the SEC's database.

Key Features

Company Discovery: Find companies by name or ticker with real-time SEC data
Complete Filing Access: Full company submission histories and document details
Advanced XBRL Analysis: Extract dimensional financial facts with geographic/segment breakdowns
Intelligent Fact Search: Find specific financial values with dimensional context
Business Intelligence: Automated fact classification and table generation
Multi-API Integration: Robust fallback mechanisms across SEC endpoints
Real-time Data: Direct access to SEC's live EDGAR database
MCP Compatible: Works seamlessly with Cursor, Claude Desktop, and other MCP clients

European Filings - Sister Project

Looking for European company financial data? Check out our companion server:

EU Filings MCP Server - Access financial filings from 27+ EU countries via ESEF (European Single Electronic Format)

98% feature parity with this SEC server, optimized for European regulatory frameworks.

Usage

Add the server to your MCP client configuration:

{
  "mcpServers": {
    "sec-mcp-server": {
      "command": "node",
      "args": ["/path/to/sec-mcp-server/build/index.js"],
      "env": {}
    }
  }
}

Dimensional XBRL Capabilities

Fact Table Generation

Extract precise financial facts with complete dimensional context:

{
  "method": "build_fact_table",
  "cik_or_ticker": "JNJ",
  "target_value": 638000000,
  "tolerance": 50000000
}

Returns dimensional facts like:

$638.0M = J&J Electrophysiology Non-US Revenue (Q1 2025)
Complete dimensional breakdown: Geography + Business Segment + Subsegment
Full XBRL context: us-gaap:NonUsMember + jnj:MedTechMember + jnj:ElectrophysiologyMember

Business Intelligence Extraction

Automatically classifies and analyzes financial facts:

Subsegment Revenue: Product-line specific performance
Geographic Revenue: International vs domestic breakdowns
Segment Revenue: Business division analysis
Comparative Analysis: Cross-product and cross-geography insights

Complete API Reference

The server provides a unified sec_edgar tool with 10 powerful methods:

Core Company Operations

1. Search Companies (`search_companies`)

Find companies by name or ticker using SEC's official database.

{
  "method": "search_companies",
  "query": "Johnson & Johnson"
}

2. Get Company CIK (`get_company_cik`)

Convert ticker symbols to Central Index Keys with validation.

{
  "method": "get_company_cik",
  "ticker": "JNJ"
}

3. Get Company Submissions (`get_company_submissions`)

Retrieve complete filing history with enhanced metadata.

{
  "method": "get_company_submissions",
  "cik_or_ticker": "0000200406"
}

Financial Data Access

4. Get Company Facts (`get_company_facts`)

Access all XBRL financial data with structured organization.

{
  "method": "get_company_facts",
  "cik_or_ticker": "JNJ"
}

5. Get Company Concept (`get_company_concept`)

Extract specific financial concepts with historical trends.

{
  "method": "get_company_concept",
  "cik_or_ticker": "JNJ",
  "taxonomy": "us-gaap",
  "tag": "RevenueFromContractWithCustomerExcludingAssessedTax"
}

6. Get Frames Data (`get_frames_data`)

Analyze aggregated data across companies and periods.

{
  "method": "get_frames_data",
  "taxonomy": "us-gaap",
  "tag": "Assets",
  "unit": "USD",
  "frame": "CY2024Q1I"
}

Advanced Dimensional Analysis

7. Get Dimensional Facts (`get_dimensional_facts`)

Extract facts with complete dimensional context from XBRL instance documents.

{
  "method": "get_dimensional_facts",
  "cik_or_ticker": "JNJ",
  "accession_number": "0000200406-25-000119",
  "search_criteria": {
    "concept": "RevenueFromContractWithCustomerExcludingAssessedTax",
    "valueRange": {
      "min": 588000000,
      "max": 688000000
    },
    "dimensions": {
      "subsegment": "Electrophysiology"
    }
  }
}

8. Search Facts by Value (`search_facts_by_value`)

Find financial facts around specific target values with filters.

{
  "method": "search_facts_by_value",
  "cik_or_ticker": "JNJ",
  "target_value": 638000000,
  "tolerance": 50000000,
  "filters": {
    "concept": "Revenue",
    "formType": "10-Q"
  }
}

9. Build Fact Table (`build_fact_table`)

Generate comprehensive dimensional fact tables with business intelligence.

{
  "method": "build_fact_table",
  "cik_or_ticker": "JNJ",
  "target_value": 638000000,
  "tolerance": 50000000,
  "options": {
    "maxRows": 25,
    "showDimensions": true,
    "sortBy": "deviation"
  }
}

Utility Operations

10. Filter Filings (`filter_filings`)

Enhanced filtering with date ranges and form types.

{
  "method": "filter_filings",
  "filings": [...],
  "form_type": "10-Q",
  "start_date": "2024-01-01",
  "end_date": "2024-12-31"
}

🏗️ Enhanced Architecture

Multi-Tier API Access Strategy

Primary: Direct iXBRL document parsing from EDGAR Archives
Secondary: SEC Submissions API for filing discovery and metadata
Tertiary: Company Facts API with dimensional inference
Emergency: Known dimensional structure mapping

SEC API Compliance

Official Endpoints: Uses data.sec.gov APIs per SEC guidelines
Proper User-Agent: SEC-Research-Tool/1.0 (contact@research.org)
Rate Limiting: Respects 10 requests/second SEC limit
Error Recovery: Graceful degradation with meaningful diagnostics

iXBRL Parser Technology

Modern Format Support: Handles Inline XBRL (HTML-embedded) instead of legacy XML
Dimensional Extraction: Parses <ix:nonFraction>, <ix:fraction>, and context relationships
Business Classification: Automatically categorizes facts by type and dimensional scope
Context Resolution: Maps XBRL contexts to readable dimensional breakdowns

Real-World Use Cases

Investment Analysis

{
  "method": "build_fact_table",
  "cik_or_ticker": "AAPL",
  "target_value": 100000000000,
  "tolerance": 10000000000
}

Find all facts around $100B for Apple with dimensional context

Competitive Intelligence

{
  "method": "search_facts_by_value",
  "cik_or_ticker": "TSLA",
  "target_value": 20000000000,
  "filters": {
    "concept": "Revenue",
    "dimensions": {"geography": "International"}
  }
}

Analyze Tesla's international revenue performance

Regulatory Compliance Monitoring

{
  "method": "get_dimensional_facts",
  "cik_or_ticker": "JPM",
  "search_criteria": {
    "concept": "LoanLossProvision",
    "valueRange": {"min": 1000000000, "max": 5000000000}
  }
}

Monitor JPMorgan's loan loss provisions with risk segmentation

Cross-Company Benchmarking

{
  "method": "get_frames_data",
  "taxonomy": "us-gaap",
  "tag": "OperatingIncomeLoss",
  "unit": "USD",
  "frame": "CY2024Q3I"
}

Compare operating income across all companies for Q3 2024

Installation & Setup

Quick Start with Claude Desktop

Add to your Claude Desktop MCP configuration:

{
  "mcpServers": {
    "sec-edgar": {
      "command": "npx",
      "args": ["@openpharma-org/sec-mcp"]
    }
  }
}

SEC Filing Reference

Major Form Types

Form	Description	Frequency	Key Data
10-K	Annual Report	Yearly	Complete financials, business overview
10-Q	Quarterly Report	Quarterly	Unaudited financials, interim updates
8-K	Current Report	As needed	Material events, acquisitions
DEF 14A	Proxy Statement	Annually	Executive compensation, voting matters
20-F	Foreign Annual	Yearly	Non-US company annual report
S-1	Registration	As needed	IPO registration statement

XBRL Taxonomies

US-GAAP (us-gaap)

Primary financial concepts:

Assets - Total company assets
Liabilities - Total liabilities
StockholdersEquity - Shareholders' equity
RevenueFromContractWithCustomerExcludingAssessedTax - Revenue excluding taxes
NetIncomeLoss - Net income or loss
OperatingIncomeLoss - Operating income or loss
CashAndCashEquivalents - Cash and equivalents

Dimensional Axes

srt:StatementGeographicalAxis - Geographic segmentation
us-gaap:StatementBusinessSegmentsAxis - Business segment breakdown
us-gaap:SubsegmentsAxis - Product line subsegments
us-gaap:StatementEquityComponentsAxis - Equity components

Common Members

Geography: us-gaap:UsMember, us-gaap:NonUsMember
Business: *:TechnologyMember, *:HealthcareMember, *:MedTechMember
Products: *:ElectrophysiologyMember, *:OrthopedicsMember

🔍 Advanced Query Patterns

Finding Dimensional Revenue Facts

{
  "method": "get_dimensional_facts",
  "cik_or_ticker": "JNJ",
  "search_criteria": {
    "concept": "RevenueFromContractWithCustomerExcludingAssessedTax",
    "dimensions": {
      "us-gaap:StatementBusinessSegmentsAxis": "jnj:MedTechMember",
      "us-gaap:SubsegmentsAxis": "jnj:ElectrophysiologyMember"
    }
  }
}

Building Comprehensive Analysis Tables

{
  "method": "build_fact_table",
  "cik_or_ticker": "PFE",
  "target_value": 15000000000,
  "tolerance": 2000000000,
  "options": {
    "maxRows": 50,
    "sortBy": "value",
    "filters": {
      "concept": "Revenue",
      "formType": "10-Q"
    }
  }
}

Cross-Period Comparison

{
  "method": "search_facts_by_value",
  "cik_or_ticker": "AMZN",
  "target_value": 50000000000,
  "tolerance": 5000000000,
  "filters": {
    "concept": "OperatingIncome"
  }
}

Performance Optimization

Best Practices

Use CIK instead of ticker when possible for faster lookups
Cache Company Facts data for repeated concept queries
Limit fact table rows with maxRows option for large datasets
Use specific accession numbers to avoid submission lookups
Batch similar requests to respect rate limits

Resources

SEC EDGAR: Official SEC Resources
XBRL Resources: XBRL.org

Important: This is an unofficial tool. Please respect SEC's data usage guidelines and terms of service. Always verify critical financial data through official SEC sources.