Infrastructure that connects LLMs to ERPNext. Frappe Assistant Core works with the Model Context Protocol (MCP) to expose ERPNext functionality to any compatible Language Model
# Add to your Claude Code skills
git clone https://github.com/buildswithpaul/Frappe_Assistant_CoreGuides for using ai agents skills like Frappe_Assistant_Core.
Last scanned: 5/30/2026
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"status": "PASSED",
"scannedAt": "2026-05-30T15:24:28.886Z",
"npmAuditRan": true,
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}See how Frappe_Assistant_Core compares with popular alternatives.
Frappe_Assistant_Core is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by buildswithpaul. Infrastructure that connects LLMs to ERPNext. Frappe Assistant Core works with the Model Context Protocol (MCP) to expose ERPNext functionality to any compatible Language Model. It has 320 GitHub stars.
Yes. Frappe_Assistant_Core passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/buildswithpaul/Frappe_Assistant_Core" and add it to your Claude Code skills directory (see the Installation section above).
Frappe_Assistant_Core is primarily written in Python. It is open-source under buildswithpaul on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh Frappe_Assistant_Core against similar tools.
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Talk to your ERPNext site. FAC lets Claude, ChatGPT, and other MCP-ready LLMs work directly with your invoices, customers, stock, workflows, and custom apps — inside your ERPNext permissions, with every call logged.
FAC 3.0 introduces FAC Chat — an opt-in, in-Frappe AI chat assistant powered by FAC Cloud, our managed service. What it does, what it costs and how to sign up: https://fac-suite.com.
FAC now offers two ways to use it:
/copilot,
powered exclusively by FAC Cloud. One subscription covers LLM
access across providers, conversation memory, RAG, and workflow
automation. Ships disabled by default. See
https://fac-suite.com.The split is intentional: BYO-LLM keeps the existing free MCP path untouched; FAC Chat is the managed experience for teams that want the chat inside Frappe without wiring up their own LLM keys. See FAC Chat below for full details.
Once FAC is installed, your team can ask an LLM for things they'd normally do by hand:
"Show me overdue invoices from our top five customers."
"Update this lead's status to Qualified and set next action date to Monday."
"Run the monthly revenue report and summarise the top movers."
"How much stock of SKU-1234 do we have across all warehouses?"
Behind that simple interaction, FAC exposes 24 built-in tools for the things your team does every day — document CRUD, search, reports, workflows, analytics, file extraction, and dashboards. Admins can publish Skills (reusable instructions that teach the LLM how to handle a specific job) and Prompt Templates (saved starting points users can pick from the admin UI) so answers stay consistent and use the right reports. The LLM authenticates over OAuth 2.0 as a real ERPNext user, so it only sees data that user can already see in the desk. Every call is recorded in the Assistant Audit Log.
It's a Frappe app, so developers can extend the toolset from their own Frappe apps through a hook — your data model, your business logic, scoped per your app.
Your data stays in your site. You control which LLM connects.
Two install paths depending on how you run Frappe.
Marketplace: https://cloud.frappe.io/marketplace/apps/frappe_assistant_core
cd frappe-bench
bench get-app https://github.com/buildswithpaul/Frappe_Assistant_Core
bench --site <your-site> install-app frappe_assistant_core
Node 22+ is needed only to build the FAC Chat UI. The assets are
built on your instance rather than shipped pre-built, so a bench on an
older Node will fail that build step. Upgrade Node to 22 and re-run
bench build. A site using FAC purely as an MCP server does not need
this.
Requires Frappe v15 or v16 and Python 3.10+.
Once installed, the same four steps work for any MCP-compatible client. Example shown for Claude Desktop:
For ChatGPT, Claude Web, and MCP Inspector walkthroughs, see the Quick Start on the docs site.
FAC Chat is an opt-in, SaaS-powered chat experience that ships inside
FAC. Where the MCP server lets external LLM clients (Claude Desktop,
Cursor, ChatGPT desktop) talk to your Frappe data with your own LLM
keys, FAC Chat brings the conversation inside Frappe itself — a widget
on every Desk page and a full-screen SPA at /copilot — powered by a
FAC Cloud subscription.
Plans, pricing and sign-up live at https://fac-suite.com; this section covers only what the app itself does.
| Option | What it is | LLM | Cost | Where the chat lives |
|---|---|---|---|---|
| BYO-LLM (MCP server) | The original FAC. Exposes Frappe data over MCP to any MCP-ready client. | You bring your own (Anthropic, OpenAI, Gemini, Bedrock, etc.) | Free. You pay your own LLM bill. | In your external MCP client (Claude Desktop, Cursor, etc.). No chat UI inside Frappe. |
| FAC Chat (SaaS) | In-Frappe chat widget + /copilot SPA. Streaming, tool use, attachments, history, memory, RAG, workflows. |
Managed by FAC Cloud. One subscription, multiple providers. | Subscription required. Sign up flow runs inside the chat UI. | Inside Frappe Desk. |
These are mutually exclusive at the chat layer: the in-Frappe chat UI is only available through FAC Cloud. There is no BYO-LLM path for FAC Chat — if you want to bring your own LLM, use the MCP server.
Both options share the same plugin registry, the same
Assistant Audit Log, and the same OAuth-based authentication.
Enabling FAC Chat does NOT change anything for your MCP clients — both
can run side by side.
That is the whole thing — no bench restart. The chat hooks are
registered unconditionally and every consumer checks the toggle at
request time, so other workers pick up the new state on their next
request.
A discovery banner on the Desk landing page will also walk admins through enabling chat — it appears once per admin and can be dismissed.
After enabling:
/copilot.FAC gives you two ways to shape what the LLM does with your data.
Skills are reusable instructions you give the LLM — stored as
FAC Skill documents inside your site. Each skill has a skill_id,
a description, and markdown content describing how to handle a specific
task using the available tools. The LLM lists skills on connect and
pulls them on demand, so every time someone asks about, say, the
monthly sales close, the answer is consistent and uses the right
reports.
Prompt Templates are saved starting points for the user's side of the conversation — Jinja-templated prompts with typed arguments (dropdowns, dates, booleans). Authors publish them from the admin page; users pick one, fill in the arguments, and the rendered prompt is sent to the LLM. Use them for frequently-asked analyses like "Sales Analysis", "Manufacturing Analysis", or your own industry-specific workflows.
Both live in Frappe, so they're version-controlled with your site,
shareable across users, and can be shipped by external Frappe apps
through the assistant_skills hook.
FAC ships 22 tools across four plugins: Core (Frappe operations), Data Science (Python execution, analytics, file extraction), Visualization (dashboards and charts), and Custom Tools