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 norman-finance · MCP Server · ★ 55
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is norman-mcp-server safe to install? View the security audit →
Norman MCP Server Your finances, inside your AI assistant. Norman connects your accounting, invoicing, and VAT filing directly to Claude, Cursor, and any MCP-compatible AI. https://mcp.norman.finance/mcp Claude · ChatGPT · Cursor · OpenClaw · n8n · Any MCP Client What you can do Invoicing — Create, send, and track invoices including recurring and ZUGFeRD e-invoices Bookkeeping — Categorize transactions, match receipts, and verify entries C
| Stars | 55 |
| Forks | 13 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 67.1179988925001/100 |
| Open Issues | 1 |
| Last Updated | 2026-09-18 |
| Created | 2025-04-16 |
| Platforms | claude-code, cli, gemini, mcp, python |
| Est. Tokens | ~15k |
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norman-mcp-server is AI-powered bookkeeping and tax filing automation for entrepreneurs at the heart of the European economy. It is categorized as a MCP Server with 55 GitHub stars.
norman-mcp-server is primarily written in Python. It covers topics such as bookkeeping, claude, cursor-plugin.
You can find installation instructions and usage details in the norman-mcp-server GitHub repository at github.com/norman-finance/norman-mcp-server. The project has 55 stars and 13 forks, indicating an active community.
norman-mcp-server is released under the MIT license, making it free to use and modify according to the license terms.
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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: