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)

Related MCP server: EdgarTools MCP

Prerequisites

• Python 3.10+ — Download Python

• uv — Install uv

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 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.

Tool 2: download_sec_report

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

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.

Tool 4: keyword_search

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

Tool 5: get_report_pages

Read full page content by page number range.

Tool 6: get_report_toc

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

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

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