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EDGAR (SEC filings)

mcpwright/edgar-mcp
1STDIOregistry active
Summary

Plugs SEC EDGAR filings directly into your agent with 11 read-only tools that hit public endpoints. You get issuer lookup by ticker or name (including private filers), filing search and retrieval, parsed Reg CF/D/A offering details with financials and investor counts, XBRL facts for headline numbers like revenue and assets, and insider trading data from Section 16 forms. Responses are cached in-memory to stay under the SEC's rate limits. Useful when you need to pull live securities data, screen recent raises by state or form type, or let an LLM summarize filing text without leaving the conversation. Works with any MCP client over stdio.

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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), 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"):

uvx mcpwright-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                       # 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

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 (Form 1-A) support in get_recent_offerings
  • 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 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

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Configuration

EDGAR_MCP_USER_AGENT

Descriptive User-Agent with contact info, which the SEC requests (e.g. 'your-app you@example.com'). Optional but recommended.

Categories
AI & LLM Tools
Registryactive
Packagemcpwright-edgar
TransportSTDIO
UpdatedJun 4, 2026
View on GitHub

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