No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by stefanoamorelli · MCP Server · ★ 357
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is sec-edgar-mcp safe to install? View the security audit →
SEC EDGAR MCP MCP server for accessing SEC EDGAR filings. Connects AI assistants to company filings, financial statements, and insider trading data with exact numeric precision. Built on edgartools. https://github.com/user-attachments/assets/d310eb42-b3ca-467d-92f7-7d132e6274fe See demo video <img style="max-width:300px;" src="https://cdn.loom.com/sessio
| Stars | 357 |
| Forks | 94 |
| Language | Python |
| Category | MCP Server |
| License | AGPL-3.0 |
| Quality Score | 71.3241644761286/100 |
| Open Issues | 8 |
| Last Updated | 2026-09-15 |
| Created | 2025-04-01 |
| Platforms | mcp, python |
| Est. Tokens | ~14k |
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sec-edgar-mcp is A SEC EDGAR MCP (Model Context Protocol) Server. It is categorized as a MCP Server with 357 GitHub stars.
sec-edgar-mcp is primarily written in Python. It covers topics such as ai, artificial-intelligence, edgar.
You can find installation instructions and usage details in the sec-edgar-mcp GitHub repository at github.com/stefanoamorelli/sec-edgar-mcp. The project has 357 stars and 94 forks, indicating an active community.
sec-edgar-mcp is released under the AGPL-3.0 license, making it free to use and modify according to the license terms.
The top alternatives to sec-edgar-mcp on Agent Skills Hub include jadx-mcp-server, mysql_mcp_server, atlassian-mcp-server. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: