Moodle MCP Server for LlamaIndexGive LlamaIndex instant access to 12 tools to Create Courses, Create Users, Enrol Users, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Moodle as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
Ask AI about this App Connector for LlamaIndex
The Moodle app connector for LlamaIndex is a standout in the Productivity category — giving your AI agent 12 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Moodle. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Moodle?"
)
print(response)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Moodle MCP Server
Connect your Moodle instance to any AI agent and manage your learning platform through natural conversation.
LlamaIndex agents combine Moodle tool responses with indexed documents for comprehensive, grounded answers. Connect 12 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
What you can do
- Courses — List, create, and browse course content sections
- Users — Search, create, and manage learner profiles
- Enrolment — Enrol users into courses and view enrolled learners
- Grades — Retrieve grade items and student results per course
- Assignments — List assignments for specific courses
- Categories — Browse course organization categories
- Files — Access files attached to course modules
- Site Info — Retrieve Moodle instance metadata
The Moodle MCP Server exposes 12 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 12 Moodle tools available for LlamaIndex
When LlamaIndex connects to Moodle through Vinkius, your AI agent gets direct access to every tool listed below — spanning e-learning, course-management, student-tracking, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Requires fullname, shortname, and categoryid. Create new courses
Requires username, password, firstname, lastname, and email. Create new users in Moodle
Enrol users into a course
Get contents of a specific course
Get users enrolled in a course
Get Moodle site information
Get grades for a user in a course
List assignments for courses
List course categories
List all available courses
List files in a specific area
g., username, email) and value. Search for users in Moodle
Connect Moodle to LlamaIndex via MCP
Follow these steps to wire Moodle into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the Moodle MCP Server
LlamaIndex provides unique advantages when paired with Moodle through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Moodle tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Moodle tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Moodle, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Moodle tools were called, what data was returned, and how it influenced the final answer
Moodle + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Moodle MCP Server delivers measurable value.
Hybrid search: combine Moodle real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Moodle to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Moodle for fresh data
Analytical workflows: chain Moodle queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Moodle in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Moodle immediately.
"List all courses and show enrolment counts."
"Get grades for student ID 42 in the Python course."
"Create a new course 'AI Ethics' in category 1 and enrol 3 students."
Troubleshooting Moodle MCP Server with LlamaIndex
Common issues when connecting Moodle to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpMoodle + LlamaIndex FAQ
Common questions about integrating Moodle MCP Server with LlamaIndex.