by superWorldSavior · MCP Server · ★ 107
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is mcp-erpnext safe to install? View the security audit →
English | 繁體中文 @casys/mcp-erpnext [!IMPORTANT] Installing the 3.1 beta: for npm/Node use ; for Deno use . Both follow the current prerelease — JSR has no dist-tags, hence the range there. Exact versions are in the CHANGELOG. The beta adds the generic document viewer and attachment workflows, so test it with the MCP host your users actually run before replacing a stable deployment. Let any MCP-compatible AI agent operate your ERPNext / Frappe instance — documents, workflows, and interactive viewers inside the host (Claude Desktop, Claude Code, VS Code Copilot, or custom). Works with self-hosted and
npx -y @casys/mcp-erpnext --categories=sales,inventory
Taken from the project's README on GitHub. Check the security audit before running it.
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 →
| Stars | 107 |
| Forks | 40 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 70/100 |
| Open Issues | 4 |
| Last Updated | 2026-10-16 |
| Created | 2026-02-18 |
| Platforms | claude-code, mcp, node |
| Est. Tokens | ~19k |
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mcp-erpnext is Let AI agents operate your ERPNext — documents, workflows, and interactive viewers. It is categorized as a MCP Server with 107 GitHub stars.
mcp-erpnext is primarily written in TypeScript. It covers topics such as ai-agents, claude, claude-desktop.
The README on GitHub (github.com/superWorldSavior/mcp-erpnext) gives: npx -y @casys/mcp-erpnext --categories=sales,inventory. Usage details are in the same README.
mcp-erpnext is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to mcp-erpnext on Agent Skills Hub include mcp-erpnext, notion-mcp-server, erpnext-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: