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.
| 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. |
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"):
Claude Code
claude mcp add edgar -- uvx mcpwright-edgar
Claude Desktop
Add to claude_desktop_config.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:
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)
Any other MCP client (Cursor, VS Code, Cline, Goose, Zed, …)
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-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 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=0 to disable.
Develop
git clone https://github.com/mcpwright/edgar-mcp && cd edgar-mcp
uv sync
uv run pytest
uv run ruff check . && uv run ruff format --check .
uv run mypy src tests
uv run mcp dev src/edgar_mcp/server.py
Roadmap
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 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/
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