How do I get an eduMe API Key?

Log in to your eduMe dashboard, navigate to **Settings > API**, and you can generate or retrieve your unique API Key from there. API access may require an enterprise-level plan.

Can the agent assign courses to users?

This integration currently focuses on listing and auditing training data. Assigning courses or creating new users should be managed via the eduMe dashboard or specific enrollment API endpoints.

Does the integration show real-time completion?

Yes, you can use the list_training_courses or get_user_training_profile tools to retrieve the latest completion rates and statuses as reported by the eduMe platform.

eduMe MCP Server for LangChain 10 tools — connect in under 2 minutes

Name: eduMe
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect eduMe through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "edume": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using eduMe, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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* 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 eduMe MCP Server

Integrate eduMe, the leading mobile-first training platform for the deskless workforce, directly into your AI workflow. Manage your training courses and modules, track trainee profiles and completion rates, monitor team performance, and oversee your organizational learning metadata using natural language.

LangChain's ecosystem of 500+ components combines seamlessly with eduMe through native MCP adapters. Connect 10 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

What you can do

Course Oversight — List and retrieve detailed information and completion metrics for all your mobile training courses.
Trainee Intelligence — Monitor user training profiles, identifying completed courses, active enrollments, and organizational team memberships.
Team Management — Access and monitor all training teams and user groups configured in your eduMe account.
Learning Auditing — Retrieve high-level summaries of team activity, course engagement, and organizational training health.

The eduMe MCP Server exposes 10 tools through the Vinkius. Connect it to LangChain 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 eduMe to LangChain via MCP

Follow these steps to integrate the eduMe MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 10 tools from eduMe via MCP

Why Use LangChain with the eduMe MCP Server

LangChain provides unique advantages when paired with eduMe through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine eduMe MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across eduMe queries for multi-turn workflows

eduMe + LangChain Use Cases

Practical scenarios where LangChain combined with the eduMe MCP Server delivers measurable value.

RAG with live data: combine eduMe tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query eduMe, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain eduMe tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every eduMe tool call, measure latency, and optimize your agent's performance

eduMe MCP Tools for LangChain (10)

These 10 tools become available when you connect eduMe to LangChain via MCP:

get_course_details

Get detailed settings and module list for a specific training course

get_edume_account_metadata

Retrieve metadata and limits for your eduMe account

get_user_training_profile

Get full training history and profile for a specific user

list_latest_training_content

Identify the most recently created or updated training courses

list_top_performing_courses

Identify courses with the highest completion or engagement rates (mock logic)

list_trained_users

List all users registered in your eduMe training platform

list_training_courses

List all mobile training courses available in eduMe

list_training_teams

List all teams and user groups configured in your eduMe account

quick_team_training_audit

Retrieve a high-level summary of team activity and member counts

search_trainees_by_keyword

Search for users using a name keyword or external identifier

Example Prompts for eduMe in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with eduMe immediately.

"List all mobile training courses."

"Show me the training profile for user 'john_doe'."

"Which teams have the lowest course engagement?"

Troubleshooting eduMe MCP Server with LangChain

Common issues when connecting eduMe to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

eduMe + LangChain FAQ

Common questions about integrating eduMe MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.