edX MCP Server for LlamaIndex 8 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add edX 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 MCP SERVER
Vinkius supports streamable HTTP and SSE.
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 edX. "
"You have 8 tools available."
),
)
response = await agent.run(
"What tools are available in edX?"
)
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 edX MCP Server
Connect to edX and explore the world's largest online learning platform through natural conversation — no API key needed.
LlamaIndex agents combine edX tool responses with indexed documents for comprehensive, grounded answers. Connect 8 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
- Course Search — Search thousands of courses by topic, university, level and language
- Course Details — Get full course info including descriptions, prerequisites and effort estimates
- Course Runs — Find upcoming and current course offerings with start dates and enrollment links
- Programs — Browse MicroMasters, Professional Certificates, XSeries and Bootcamps
- Organizations — Explore all partner universities and institutions (Harvard, MIT, Google, IBM)
- Subjects — Discover all subject categories available on the platform
The edX MCP Server exposes 8 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.
How to Connect edX to LlamaIndex via MCP
Follow these steps to integrate the edX MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 8 tools from edX
Why Use LlamaIndex with the edX MCP Server
LlamaIndex provides unique advantages when paired with edX through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine edX tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain edX tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query edX, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what edX tools were called, what data was returned, and how it influenced the final answer
edX + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the edX MCP Server delivers measurable value.
Hybrid search: combine edX real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query edX 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 edX for fresh data
Analytical workflows: chain edX queries with LlamaIndex's data connectors to build multi-source analytical reports
edX MCP Tools for LlamaIndex (8)
These 8 tools become available when you connect edX to LlamaIndex via MCP:
get_course
Returns title, description, organization, level, subjects, pacing, estimated effort, prerequisites and available course runs. Get detailed info for a specific edX course
get_course_run
Get details for a specific course run
get_course_runs
Optionally filter by course key and status (upcoming, current, archived). Get course runs (scheduled offerings) for courses
get_organizations
Returns organization names, descriptions, logos and course counts. Includes Harvard, MIT, Berkeley, Google, IBM and many more. Get partner organizations that offer courses on edX
get_program
Get details for a specific edX program
get_subjects
Returns subject names, descriptions and course counts. Useful for discovering what topics are covered on the platform. Get course subject categories
search_courses
Supports free-text search, filtering by organization, level (beginner/intermediate/advanced), language, subject. Returns course titles, descriptions, organizations, levels, subjects and enrollment links. Search for online courses on edX
search_programs
Includes MicroMasters, Professional Certificates, XSeries and Bootcamps. Returns program titles, descriptions, course counts and type. Search for edX programs (MicroMasters, Professional Certificates, XSeries)
Example Prompts for edX in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with edX immediately.
"Find machine learning courses from Harvard."
"Show me all MicroMasters programs in Data Science."
"What organizations offer courses on edX?"
Troubleshooting edX MCP Server with LlamaIndex
Common issues when connecting edX to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpedX + LlamaIndex FAQ
Common questions about integrating edX MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect edX with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect edX to LlamaIndex
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.