Borrowing it
Nothing to install: this file belongs to Casys-AI/mcp-erpnext. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Casys-AI/mcp-erpnext/main/AGENTS.mdgit clone --depth 1 https://github.com/Casys-AI/mcp-erpnextWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/casys-ai/mcp-erpnext/agents-md)<a href="https://agentmods.dev/instructions/casys-ai/mcp-erpnext/agents-md"><img src="https://agentmods.dev/badge/instructions/casys-ai/mcp-erpnext/agents-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/casys-ai/mcp-erpnext/agents-md"><img src="https://agentmods.dev/badge/instructions/casys-ai/mcp-erpnext/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.06458 | $0.06458 |
| Opus 5 | $0.03229 | $0.03229 |
| Sonnet 5 | $0.01292 | $0.01292 |
| Haiku 4.5 | $0.00646 | $0.00646 |
Grade A, and why
mcp-erpnext AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 539 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
Repository guidelines for AI coding agents working on this codebase.
- Repo: https://github.com/Casys-AI/mcp-erpnext
- In chat replies, file references must be repo-root relative only (example:
src/tools/sales.ts:42); never absolute paths.
Project Overview
MCP server that lets AI agents operate an ERPNext/Frappe instance: documents,
workflows, and interactive UI viewers. Published as @casys/mcp-erpnext on npm
(Node bundle) and JSR (Deno).
Project Structure & Module Organization
- Entry points:
mod.ts(JSR public API),server.ts(MCP server — stdio + HTTP). - Config:
deno.jsonis the primary config (version, tasks, import map).src/ui/package.jsonmanages UI-only npm deps (React, Vite, Recharts). - Source code: all under
src/. Server-side TypeScript uses Deno conventions; UI viewers use Vite/React with standard npm imports. - Tool categories: one file per category under
src/tools/(sales.ts,inventory.ts,accounting.ts, etc.). All registered insrc/tools/mod.ts. - Tests: colocated with source files (Deno convention) —
foo.ts/foo_test.ts. Not all modules have tests yet; the convention is the target, not a guarantee. - UI viewers: each viewer is a standalone React app under
src/ui/{viewer-name}/, bundled to a single HTML file. Built output goes tosrc/ui/dist/(gitignored but included in published artifacts viadeno.jsonpublish config). - Kanban:
src/kanban/contains types, definitions, field-utils, and per-DocType adapters inadapters/. - Cache:
src/cache/— pluggableCacheinterface,MemoryCache/NoopCacheimplementations, app-wide singleton. - Runtime adapters:
src/runtime.ts(Deno) andsrc/runtime.node.ts(Node.js) — the build script swaps them. - Scripts:
scripts/build-node.shproduces the npm bundle. - Docs:
docs/contains roadmap, known issues, and coverage notes. - Keep UI-only deps in
src/ui/package.json; do not add them todeno.json. Conversely, server-side deps go in thedeno.jsonimport map.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 539 lines · 6,458 tokens per session scan A f114e4f0c160
mcp-erpnext AGENTS.md is an instructions file published in the GitHub repository Casys-AI/mcp-erpnext (94 stars, last pushed 2d ago), licensed MIT. It adds 6,458 tokens to every session, about $0.0323 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other instructions, from other repositories
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.