mcp-erpnext
Enables AI agents to interact directly with ERP data and workflows, reducing manual data entry and bridging the gap between LLM reasoning and core business o…
Let AI agents operate your ERPNext — documents, workflows, and interactive viewers
- Ask Claude to retrieve specific documents from your ERPNext database
- Generate summaries of existing workflows and business processes
- Find information stored within your ERPNext document records
Enables AI agents to interact directly with ERP data and workflows, reducing manual data entry and bridging the gap between LLM reasoning and core business operations.
Operations managers and engineering teams automating enterprise resource planning tasks through agentic workflows.
https://github.com/Casys-AI/mcp-erpnext
By Casys-AI
How to Get It
claude mcp add mcp-erpnext -- npx -y mcp-erpnext
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
Once it’s connected, paste this into Claude:
Retrieve specific documents from my ERPNext database
Trust Signals Auto-scanned
Data & Access
Community Pulse Emerging
Discussed on Hacker News
- MCP Server for ERPNext / Frappe ERP – MCP Apps — Hacker News · 2 pts
1 mentions across 1 sources
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 116 GitHub stars; contributors unknown; last commit 0d ago; license MIT.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
How to evaluate tools before deploying →
Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.
Evaluation
Scored from trust signals (evidence-eval-v1): 116 GitHub stars; contributors unknown; last commit 0d ago; license MIT.