
Moodle Mcp Server Aql
io.github.csmediapro由 GitHub 帳號 csmediapro 發布v0.1.6更新於 Oct 24, 2026
Query Moodle LMS data through natural language. Attach your agent to your LMS data.
概覽
讓助理以自然語言查詢 Moodle LMS 資料,包括課程、選課、作業、分類與使用者,透過 Moodle Web Services API 取得。
- 可以做什麼
- 將 AI 代理連接到 Moodle 實例的 Web Services API,並提供唯讀查詢工具。核心工具涵蓋課程目錄與分類下鑽、課程詳細資料、已選課使用者及其角色、作業與截止日期、分類階層、站台中介資料、使用者詳細資料、某使用者的課程、使用者搜尋,以及依名稱搜尋課程。另有重新整理工具可探索標準與自訂使用者欄位。選用的付費外掛可增加報表、分析、目錄與合規工具。
- 適用情境
- 適合需要詢問 Moodle 站台狀況時使用,例如課程清單、選課人員、有哪些作業、站台資訊,而不必建立報表、撰寫 SQL 或匯出 CSV。適用於已具備 Moodle Web Services 存取權限並擁有相容 MCP 用戶端的管理員、教師或支援人員。
- 執行需求
- 透過 npm 套件 moodle-mcp-server-aql 以 stdio 方式在本機執行,需要 Node.js 20+。需要一個已啟用 Web Services 的 Moodle 實例,以及 Moodle Web Services API 權杖,透過 MOODLE_TOKEN 密鑰與 MOODLE_URL 基礎網址提供。自然語言介面需要相容 MCP 的 AI 用戶端或模型供應方。僅支援桌面端。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 Moodle Mcp Server Aql,將其新增到工作區。
- 為需要使用其工具的對話啟用該服務。
Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。
其他 MCP 客戶端
參照 儲存庫 中的啟動說明。
README
moodle-mcp-server — AI-Powered LMS Analytics
Ask your Moodle instance anything. Get structured answers in seconds.
moodle-mcp-server is an open-source MCP (Model Context Protocol) server that connects AI agents directly to Moodle's Web Services API. It is the first reference implementation of the Agentic Query Layer (AQL) pattern — a software design pattern for giving large language models safe, permission-aware, read-only access to structured data.
Instead of learning report builders, writing SQL, or exporting CSVs, you ask questions in plain English — the AI agent queries your LMS and returns structured data.
AQL pattern: https://csmediapro.com/notes/agentic-query-layer
Project home: https://csmediapro.com/products/moodle-mcp-server
npm package: https://www.npmjs.com/package/moodle-mcp-server-aql
MCP Registry: io.github.csmediapro/moodle-mcp-server-aql
Features
- Core query tools — course catalog, user enrollment, assignments, category navigation, site metadata, user lookup, and cache management
- Premium reporting plugins — optional tools such as course completion reports and recent activity can be attached through the plugin runtime
- LLM-agnostic — works with Claude, GPT, Gemini, Ollama, or any MCP-compatible AI client
- Zero LMS modification — uses Moodle's existing Web Services API, no plugin installation required
- Compliance-ready data handling — secure, efficient data processing with privacy by design
- Read-only — never modifies Moodle data, safe for production
- Plugin-extensible — drop new tool modules into a directory; tools and optional agent routing hints auto-register at runtime
Quick Start
Prerequisites
- Node.js 20+
- A Moodle instance with Web Services enabled
- A Moodle API token (Site administration → Plugins → Web services → Manage tokens)
Use With An MCP Client
Most users launch the server through an MCP client such as Claude Desktop:
Setup From Source
User field schema
User field display settings are generated per Moodle instance and stored locally at
packages/server/data/user-field-schema.json. This file is intentionally ignored by git
because it can include site-specific custom profile fields.
After connecting to a Moodle site, run the refresh_user_field_schema tool once to
discover available standard and custom user fields. A minimal example shape is included
at packages/server/data/user-field-schema.example.json.
Separately installed plugins can use this schema to flatten custom profile fields
into stable keys such as school. The premium user-directory plugin, for example,
uses it to cache and summarize full-user directory fields outside the OSS core.
Config identity
The core owns two different server identity fields:
server.id— stable machine identity, for examplemcp_8f3k2q9xserver.name— human-facing display label
If server.id is missing, the core generates one once and persists it to the resolved config file before startup continues.
Environment overrides:
MOODLE_MCP_CONFIGorMOODLE_MCP_SERVER_CONFIG— choose the config file pathSERVER_ID— explicitserver.idoverrideSERVER_NAME— explicitserver.nameoverrideSERVER_VERSION— explicitserver.versionoverride
If server.id is missing and the resolved config path is not writable, startup fails deliberately.
Using the reference client
The client will auto-detect your Moodle instance and present a chat interface where you can ask questions in plain English.
Connecting an LLM
moodle-mcp-server needs an AI model to power the natural-language interface. You bring the model — the moodle-mcp-server core and reference client support any MCP-compatible provider.
Option 1: Run Locally (Recommended for Speed & Privacy)
Running a local model keeps all data on your own hardware — nothing leaves your network. Modern quantized models run well on consumer GPUs and even CPU-only setups.
Performance: A quantized 24B model on a single RTX 3090 delivers ~1.5-second responses after the first query — faster than most cloud APIs once the system is initialized.
Via Ollama (easiest)
Then point the reference client at http://localhost:11434 (Ollama's default).
Via llama.cpp (maximum control)
Point the reference client at http://localhost:8080/v1.
Recommended local models
Option 2: Cloud Providers
Anthropic (Claude):
Select "Anthropic" in the reference client's provider dropdown. Claude Sonnet offers the most reliable tool-calling behavior.
OpenAI (GPT):
Select "OpenAI" in the provider dropdown. GPT-4o performs well on structured queries.
Ollama Cloud:
Uses the same API as local Ollama, hosted at https://ollama.com/v1. Good middle ground — faster than local cold starts, more private than big cloud providers.
Option 3: Claude Desktop (Direct MCP)
Claude Desktop connects to the moodle-mcp-server core directly over stdio — no reference client needed.
Add to your Claude Desktop config (claude_desktop_config.json):
Restart Claude Desktop. The server's tools will appear in Claude's tool list — ask questions directly.
Tools
Core Tools (free, open source — AGPL)
Premium Plugins (available separately)
- Advanced Reporting — gradebooks, cross-course comparison, custom report builder
- User Analytics — progress tracking, engagement scoring, risk flags
- User Directory — cached directory listing and structured filtering across standard and custom profile fields
- Compliance Pack — certification tracking, expiration alerts, audit exports
Architecture
This project is a reference implementation of the Agentic Query Layer (AQL) pattern — a layer that sits between an AI agent and your data, providing permission-aware, read-only, plain-language access without exposing the underlying data to the model.
Transport modes
- Stdio —
dist/index.js— runs as a subprocess, used by Claude Desktop and similar clients
The OSS core intentionally ships with stdio only. Any network-facing wrapper, remote supervision, or premium plugin attachment belongs in a separate commercial node agent or wrapper.
Plugin docs
License
AGPL v3 — see LICENSE.
This means you can:
- ✅ Use the
moodle-mcp-servercore for free, in any environment - ✅ Modify the source code for your needs
- ✅ Build and distribute derivative works
You cannot:
- ❌ Repackage the
moodle-mcp-servercore as a closed-source competing commercial product - ❌ Offer it as a network service without sharing your modifications
Trademark Notice
Moodle is a trademark of Moodle Pty Ltd. moodle-mcp-server is an independent CSMediaPro project and is not affiliated with, endorsed by, sponsored by, or officially connected to Moodle Pty Ltd or the Moodle project. The name is used descriptively to identify compatibility with Moodle LMS.
Built by CSMediaPro
moodle-mcp-server is built and maintained by CSMediaPro, a software development company specializing in AI integration, systems engineering, and workflow automation. It is the first reference implementation of the Agentic Query Layer (AQL) pattern.
- AQL pattern: https://csmediapro.com/notes/agentic-query-layer
- Contact: [email protected]
來源:README.md,提交 9d7e300
工具
0版本歷史
3- v0.1.6最新Sep 26, 2026
- v0.1.5Sep 26, 2026
- v0.1.4Sep 16, 2026
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