EDGAR (SEC filings)

io.github.mcpwright由 GitHub 帳號 mcpwright 發布v0.1.3更新於 Oct 24, 2026

SEC filings in your agent: issuers, Reg CF/D/A raises, XBRL financials, insider trades.

發布方自己的服務:edgar.tools SEC Intelligence

已驗證STDIO僅桌面金融資料與分析

概覽

AI 產生的概覽

以唯讀方式存取 SEC EDGAR 申報文件,讓助理解析發行人、檢索申報文件,並取得財務資料與內部人交易。

可以做什麼
透過公開的 SEC EDGAR 端點提供十一個唯讀工具。它能將股票代號或公司名稱解析為 CIK 與法定名稱,列出並全文檢索申報文件,並開啟單一申報文件及其所有文件。它也能解析 Form D 與 Form C 募資、擷取 XBRL 主要財務資料,並回報內部人與 Form 4 交易。
適用情境
當助理需要 SEC 申報資料時使用:公司研究、查看近期 Reg CF、Reg D 或 Reg A 發行、閱讀特定申報文件,或了解內部人交易。適合想在代理中直接查詢申報文件、而不手動瀏覽 EDGAR 的分析師與開發者。
執行需求
以 PyPI 套件 mcpwright-edgar 透過 stdio 在本機執行,需要 Python 3.12+ 以及 uvx 等啟動器。不需要 API 金鑰或帳號。需要可連線至 SEC EDGAR 服務的網路。選用環境變數 EDGAR_MCP_USER_AGENT 可設定傳送給 SEC 的 User-Agent。
安裝前請注意
所有工具皆為唯讀,不會要求任何憑證,但 EDGAR_MCP_USER_AGENT 中設定的值會隨每次請求傳送給 SEC,因此不要在其中填入敏感資訊。請求只會送往公開的 SEC 端點;回應僅快取於記憶體,不會寫入磁碟。SEC 限速約為每秒 10 次請求,用戶端會自動節流並重試。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 EDGAR (SEC filings),將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

edgar-mcp

SEC EDGAR filings, inside your agent. An MCP server that lets an LLM resolve companies, search filings, and pull recent securities offerings straight from the SEC — built on Anthropic's official mcp Python SDK.

All tools are read-only and hit public SEC endpoints (no API key required).

Status: 11 tools, working today (see below). Published on PyPI as mcpwright-edgar and in the official MCP Registry. See the roadmap for what's next.

Tools

ToolWhat it does
lookup_issuer(query, limit=10)Resolve a ticker or company name → CIK, legal name, tickers, exchange. Works for exchange-listed and private / non-exchange filers (Reg CF / Reg A issuers, funds).
list_filings(cik_or_query, form_type=None, limit=20)An issuer's most recent filings, newest first. Optional form-type filter (e.g. 10-K, C, D).
search_filings(query, forms=None, date_from=None, date_to=None, limit=20)Full-text search across filing documents.
get_recent_offerings(form="C", since=None, state=None, limit=20)Recent securities offerings, newest first — form="C" (Reg CF), "D" (Reg D), or "A" (Reg A — 1-A offering statements plus 253G2 offering circulars, where the per-share price and any "price walk-up" live), optionally filtered by issuer state (e.g. "CA").
get_filing(accession_or_url, cik=None)Open one filing: form, filing date, primary-document link, and every document in the filing.
get_form_d_details(accession_or_url, cik=None)Parse a Form D (Reg D) raise: offering amount, sold/remaining, min investment, # investors, industry, revenue range, security types, exemptions, and the officers/directors/promoters.
get_form_c_details(accession_or_url, cik=None)Parse a Form C (Reg CF) raise: target/max amount, price, security type, deadline, intermediary, employees, and a two-year financial snapshot (revenue, net income, assets, debt).
get_company_facts(cik_or_query)Headline financials from a public company's XBRL facts: latest annual revenue, gross/operating income, net income, assets, liabilities, equity, cash.
get_filing_text(url, offset=0, max_chars=20000)Fetch a document's text (HTML stripped) for reading/summarizing — paginated, since filings can exceed 1M characters.
get_insiders(cik_or_query, limit=25)A company's insiders (officers, directors, >10% owners) from recent Section 16 filings, with roles.
get_insider_trades(cik_or_query, limit=20)Recent insider transactions (Form 4): owner, role, buy/sell/grant, shares, price, shares owned after.

Install

Requires Python 3.12+. The zero-clone way to run it (the PyPI package is mcpwright-edgar; the command, server, and tools are all "edgar"):

bash
uvx mcpwright-edgar

Claude Code

bash
claude mcp add edgar -- uvx mcpwright-edgar

Claude Desktop

Add to claude_desktop_config.json:

json
{  "mcpServers": {    "edgar": { "command": "uvx", "args": ["mcpwright-edgar"] }  }}

OpenAI Agents SDK (Python)

It's a standard MCP server, so it works with any MCP-capable client — not just Claude. With the OpenAI Agents SDK:

python
from agents import Agent, Runnerfrom agents.mcp import MCPServerStdio
async def main():    async with MCPServerStdio(        name="edgar",        params={            "command": "uvx",            "args": ["mcpwright-edgar"],            "env": {"EDGAR_MCP_USER_AGENT": "your-app [email protected]"},        },    ) as edgar:        agent = Agent(            name="Analyst",            instructions="Use the EDGAR tools for SEC filings and company data.",            mcp_servers=[edgar],        )        result = await Runner.run(            agent, "Recent Reg D raises in California — who's behind the biggest?"        )        print(result.final_output)

Any other MCP client (Cursor, VS Code, Cline, Goose, Zed, …)

They all launch a stdio MCP server the same way — point yours at:

json
{  "mcpServers": {    "edgar": {      "command": "uvx",      "args": ["mcpwright-edgar"],      "env": { "EDGAR_MCP_USER_AGENT": "your-app [email protected]" }    }  }}

Hosted chat connectors (e.g. ChatGPT connectors) expect a remote MCP server over Streamable HTTP; mcpwright-edgar runs locally over stdio. Running it behind Streamable HTTP for a hosted endpoint is straightforward if you need that.

SEC etiquette: the SEC requires a descriptive User-Agent with contact info and rate-limits to ~10 req/s. Set your own via the EDGAR_MCP_USER_AGENT env var (e.g. "your-app [email protected]"). The client throttles and retries for you.

Caching: responses are cached in-memory (byte-budgeted LRU) to cut latency and SEC load — immutable filing-archive content for days, the ticker map for 24h, everything else briefly. Set EDGAR_MCP_CACHE=0 to disable.

Develop

bash
git clone https://github.com/mcpwright/edgar-mcp && cd edgar-mcpuv syncuv run pytest                       # tests (mocked SEC responses)uv run ruff check . && uv run ruff format --check .   # lint + formatuv run mypy src tests               # strict type checkinguv run mcp dev src/edgar_mcp/server.py   # poke the tools in the MCP Inspector

Roadmap

  • get_recent_offerings(form=C|D) — recent Reg CF / Reg D raises
  • get_filing(accession_or_url) — open a filing and list its documents
  • get_form_d_details(...) — parse Reg D offering data (amount, investors, people)
  • get_form_c_details(...) — parse Reg CF offering data (target/max, financials, terms)
  • get_insiders / get_insider_trades — Section 16 (Form 3/4/5) insiders & trades
  • State filter on get_recent_offerings (industry isn't filterable — EDGAR omits SIC on these listings; screen via get_form_d_details.industry_group)
  • Reg A support in get_recent_offerings (Form 1-A statements + 253G2 offering circulars)
  • get_company_facts(cik) — XBRL headline financials
  • get_filing_text — return a document's text for summarization
  • Published to PyPI (mcpwright-edgar) + the official MCP Registry (io.github.mcpwright/edgar-mcp)
  • get_form_a_details — parse Reg A (Form 1-A) offering data
  • Older-filing metadata (beyond the recent-submissions window)

Privacy

edgar-mcp runs entirely on your machine and collects, stores, or transmits no personal data — no accounts, no tracking, no telemetry. Its only outbound requests go to the U.S. SEC's EDGAR services (data.sec.gov, efts.sec.gov, www.sec.gov) to fetch the public filings you ask for; no API key is needed. One honest note: the SEC's fair-access policy asks for a descriptive User-Agent with contact info (EDGAR_MCP_USER_AGENT="your-app [email protected]") — whatever you set there is sent to the SEC with each request, and nowhere else. Responses are cached in memory only; nothing is persisted to disk.

Full policy: https://mcpwright.com/privacy/

Questions & feedback

  • Questions, ideas, or "could it do X?" → Discussions
  • Bugs & concrete feature requests → Issues

Contributions welcome — and if you build something with it, I'd love to hear about it.


Part of mcpwright · built by Devender Gollapally

來源:README.md,提交 d183909

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  1. v0.1.3最新Sep 16, 2026

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