Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
作者提供的说明(英文原文)
SEC filings in your agent: issuers, Reg CF/D/A raises, XBRL financials, insider trades.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
EDGAR_MCP_USER_AGENT你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"edgar": {
"command": "uvx",
"args": [
"mcpwright-edgar"
],
"env": {
"EDGAR_MCP_USER_AGENT": "your-value"
}
}
}
}在终端中运行这条命令
claude mcp add edgar --env EDGAR_MCP_USER_AGENT=your-value -- uvx mcpwright-edgar运行前请先填写空着的值。
粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"edgar": {
"command": "uvx",
"args": [
"mcpwright-edgar"
],
"env": {
"EDGAR_MCP_USER_AGENT": "your-value"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"edgar": {
"type": "stdio",
"command": "uvx",
"args": [
"mcpwright-edgar"
],
"env": {
"EDGAR_MCP_USER_AGENT": "your-value"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
EDGAR_MCP_USER_AGENT env这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日
注册名称已通过 GitHub 账户 mcpwright 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(0.1.3)于3个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。
同一分类中有:Spec Driven Development, Remote Desktop Commander, SuperCollider
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Make sound with SuperCollider: synths, drums, chords, melodies and soundscapes over OSC.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
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-edgarand in the
official MCP Registry. See the roadmap for what's next.
| Tool | What 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. |
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"):
uvx mcpwright-edgar
claude mcp add edgar -- uvx mcpwright-edgar
Add to claude_desktop_config.json:
{
"mcpServers": { "edgar": { "command": "uvx", "args": ["mcpwright-edgar"] } } }
It's a standard MCP server, so it works with any MCP-capable client — not just Claude. With the OpenAI Agents SDK:
from agents import Agent, Runner
from 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 you@example.com"}, }, ) 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)
They all launch a stdio MCP server the same way — point yours at:
{
"mcpServers": { "edgar": { "command": "uvx", "args": ["mcpwright-edgar"], "env": { "EDGAR_MCP_USER_AGENT": "your-app you@example.com" } } } }
Hosted chat connectors (e.g. ChatGPT connectors) expect a remote MCP server over
Streamable HTTP;
mcpwright-edgarruns 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-Agentwith contact info and rate-limits
to ~10 req/s. Set your own via the
EDGAR_MCP_USER_AGENTenv var
(e.g.
"your-app your-email@example.com"). 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=0to disable.
git clone https://github.com/mcpwright/edgar-mcp && cd edgar-mcp
uv sync uv run pytest # tests (mocked SEC responses) uv run ruff check . && uv run ruff format --check . # lint + format uv run mypy src tests # strict type checking uv run mcp dev src/edgar_mcp/server.py # poke the tools in the MCP Inspector
get_recent_offerings(form=C|D) — recent Reg CF / Reg D raisesget_filing(accession_or_url) — open a filing and list its documentsget_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 & tradesget_recent_offerings (industry isn't filterable — EDGAR omits SIC on these listings; screen via get_form_d_details.industry_group)get_recent_offerings (Form 1-A statements + 253G2 offering circulars)get_company_facts(cik) — XBRL headline financialsget_filing_text — return a document's text for summarizationmcpwright-edgar) + the official MCP Registry (io.github.mcpwright/edgar-mcp)get_form_a_details — parse Reg A (Form 1-A) offering dataedgar-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 you@example.com") — 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/
Contributions welcome — and if you build something with it, I'd love to hear about it.
Part of mcpwright · built by Devender Gollapally