agentladle/mcp-sec

agentladle/mcp-sec

It enables AI assistants (Claude, Cursor, etc.) to access SEC EDGAR data through 6 structured tools — from discovering available filings to keyword-searching within their pages.

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README

AgentLadle MCP SEC

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A MCP (Model Context Protocol) server that provides tools for discovering, downloading, parsing, and searching U.S. SEC financial reports.

It enables AI assistants (Claude, Cursor, etc.) to access SEC EDGAR data through 6 structured tools — from discovering available filings to keyword-searching within their pages.

Features

  • 6 MCP tools for SEC financial data: state-driven retrieval (search directly, fallback to download/parse only when needed)
  • Professional SEC document parsing using edgartools — accurate page-break detection and structured node-tree extraction for iXBRL filings
  • Local keyword search with TF + position-boost scoring, zero external dependencies
  • Idempotent — already-downloaded/parsed files are automatically skipped
  • Zero-config install — one line to add to your MCP client, no clone or manual setup needed
  • Pure Python, cross-platform (Windows / macOS / Linux)

Prerequisites

Note: After installing uv, restart your terminal and MCP client (e.g. Cherry Studio) to ensure the uv command is recognized.

Quick Start

Add to your MCP client configuration (Claude Desktop, Cursor, etc.):

{
  "mcpServers": {
    "mcp-sec": {
      "command": "uvx",
      "args": ["agentladle-mcp-sec"],
      "env": {
        "SEC_EMAIL": "your@email.com"
      }
    }
  }
}

That's it. uvx will automatically download the package and its dependencies from PyPI — no clone, no manual install, no path configuration.

⚠️ SEC Email Requirement: Replace your@email.com with your real email. The SEC requires a valid email in the User-Agent header. Using a fake email may result in your IP being blocked.

Alternative: pip install

If you prefer managing the environment yourself:

pip install agentladle-mcp-sec

Then configure:

{
  "mcpServers": {
    "mcp-sec": {
      "command": "agentladle-mcp-sec",
      "env": {
        "SEC_EMAIL": "your@email.com"
      }
    }
  }
}

Alternative: Run from source (local development)

Clone the repository and run directly:

git clone https://github.com/agentladle/mcp-sec.git

Then configure your MCP client:

{
  "mcpServers": {
    "mcp-sec": {
      "command": "uv",
      "args": ["run", "--directory", "/path/to/mcp-sec", "agentladle-mcp-sec"],
      "env": {
        "SEC_EMAIL": "your@email.com"
      }
    }
  }
}

Replace /path/to/mcp-sec with the actual path to the cloned repository.

Data Flow

SEC EDGAR API                     Local Files (~/.agentladle/mcp-sec/data/)
──────────────                    ──────────────────────────────
company_tickers.json   ──→       company_tickers.json         (ticker→CIK mapping)
                                     │
SEC Submissions API    ──→        html/*.htm                  (Tool 2: download)
                                     │
edgartools parsing     ──→        json/*.json                 (Tool 3: parse, page-split)
                                     │
Local TF search        ──→        search results              (Tool 4: keyword search)
Page range read        ──→        page content                (Tool 5: read pages)
TOC lookup             ──→        table of contents           (Tool 6: get TOC)

Tools

# Tool Description
1 list_sec_filings Discover available SEC filings for a company
2 download_sec_report Download a specific SEC filing as HTML
3 parse_sec_report Parse HTML into page-split JSON using edgartools
4 keyword_search Full-text keyword search with TF relevance scoring
5 get_report_pages Read report content by page number range
6 get_report_toc Get the Table of Contents page(s)

Tool 1: list_sec_filings

List available SEC filings for a company. Use this tool ONLY when the exact year/date is unspecified by the user, or when a download attempt fails due to an invalid date.

Parameter Type Required Description
ticker string ✅ Stock ticker, e.g. "AAPL"
form string ❌ Filing type filter, e.g. "10-K". Omit to list all financial report types (10-K, 10-Q, 20-F, 6-K, 8-K, 40-F)
limit int ❌ Max filings to return, default 5, max 20

Tool 2: download_sec_report

Download a specific SEC filing from EDGAR. One filing per call. Idempotent (skips if file exists and is valid).

Parameter Type Required Description
ticker string ✅ Stock ticker, e.g. "AAPL"
form string ✅ Filing type: "10-K", "10-Q", "20-F", "6-K"
report_date string ✅ Report date (fiscal period end date), e.g. "2025-01-31"

Tool 3: parse_sec_report

Parse a downloaded HTML filing into page-split JSON. Uses edgartools mark_page_breaks() + parse_html() for professional SEC document parsing.

Parameter Type Required Description
ticker string ✅ Stock ticker
form string ✅ Filing type
report_date string ✅ Report date (fiscal period end date)

Tool 4: keyword_search

Full-text keyword search across all pages. Results ranked by TF + position-boost score.

Parameter Type Required Description
ticker string ✅ Stock ticker
form string ✅ Filing type
report_date string ✅ Report date (fiscal period end date)
keywords string[] ✅ 1–5 search keywords
match_mode string ❌ "ANY" (default, any keyword matches) / "ALL" (all must match)
max_results int ❌ Max results to return, default 5, max 50

Tool 5: get_report_pages

Read full page content by page number range.

Parameter Type Required Description
ticker string ✅ Stock ticker
form string ✅ Filing type
report_date string ✅ Report date (fiscal period end date)
start_page int ✅ Start page number (1-based)
page_count int ❌ Number of pages to return, default 3, max 5

Tool 6: get_report_toc

Get the Table of Contents page(s). Searches the first 10 pages for "Table of Contents".

Parameter Type Required Description
ticker string ✅ Stock ticker
form string ✅ Filing type
report_date string ✅ Report date (fiscal period end date)

Configuration

On first run, a default config file is created at ~/.agentladle/mcp-sec/config.yaml:

sec:
  email: ""

paths:
  data_dir: "~/.agentladle/mcp-sec/data"
  html_dir: "~/.agentladle/mcp-sec/data/html"
  json_dir: "~/.agentladle/mcp-sec/data/json"

download:
  delay_between_requests: 0.2
  min_file_size: 5000

The email field is used to build the SEC-compliant User-Agent header (AgentLadleMcpSec {email}). You can configure it in three ways (in order of priority):

  1. Environment variable SEC_EMAIL — recommended, set it in your MCP client JSON config
  2. Config file — edit ~/.agentladle/mcp-sec/config.yaml and set email
  3. Default — if empty, a placeholder email is used (not recommended for production)

⚠️ SEC User-Agent Policy: The SEC requires a real email in the User-Agent header. Using the default placeholder may result in your IP being blocked.

Data Directory Structure

~/.agentladle/mcp-sec/
├── config.yaml                        # Configuration (auto-created)
└── data/
    ├── company_tickers.json           # ticker→CIK mapping (auto-downloaded & cached)
    ├── html/                          # Downloaded HTML filings
    │   ├── AAPL_10-K_2025-01-31.htm
    │   └── ...
    └── json/                          # Parsed page-split JSON
        ├── AAPL_10-K_2025-01-31.json
        └── ...

File naming convention: {TICKER}_{FORM}_{REPORT_DATE}.htm/json

Example Usage

The tools are designed with an EAFP (Easier to Ask for Forgiveness than Permission) approach. AI assistants should attempt to retrieve data directly and rely on errors to trigger downloads.

Scenario A: File already exists locally (Shortest Path)

User: "Analyze AAPL's latest 10-K management discussion"

1. keyword_search(ticker="AAPL", form="10-K", report_date="2025-01-31", keywords=["management", "discussion"])
   → Returns page snippets matching the keywords immediately.

Scenario B: File missing (Fallback triggered)

User: "What is Tesla's 2024 revenue?"

1. keyword_search(ticker="TSLA", form="10-K", report_date="2024-12-31", keywords=["revenue", "net sales"])
   → Error: File not found.
   
2. download_sec_report(ticker="TSLA", form="10-K", report_date="2024-12-31")
   → Downloads HTML to ~/.agentladle/mcp-sec/data/html/
   
3. parse_sec_report(ticker="TSLA", form="10-K", report_date="2024-12-31")
   → Parses into JSON.
   
4. keyword_search(ticker="TSLA", form="10-K", report_date="2024-12-31", keywords=["revenue", "net sales"])
   → Retries search and returns data.

Tech Stack

Component Choice Purpose
MCP Framework mcp (FastMCP) MCP server with stdio transport
HTTP Client httpx SEC API requests & file downloads
HTML Parsing edgartools + beautifulsoup4 Professional SEC iXBRL parsing (page-break detection + node tree)
Search Python built-in TF + position-boost scoring
Config pyyaml YAML configuration file

Project Structure

src/mcp_sec/
├── __init__.py
├── server.py          # MCP Server entry point
├── config.py          # Config loading (~/.agentladle/mcp-sec/config.yaml, singleton cached)
├── models.py          # Data models
├── tools/
│   ├── list_filings.py # Tool 1: list_sec_filings
│   ├── download.py    # Tool 2: download_sec_report
│   ├── parse.py       # Tool 3: parse_sec_report
│   ├── search.py      # Tool 4: keyword_search
│   ├── page.py        # Tool 5: get_report_pages
│   └── toc.py         # Tool 6: get_report_toc
└── services/
    ├── downloader.py  # SEC EDGAR download + ticker→CIK
    ├── parser.py      # HTML→JSON parsing (edgartools)
    └── searcher.py    # Local JSON search + TF scoring

License

MIT

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