OA-Y MCP Service
MCP for managing courses via HTTP API at oa-y.com.
README
OA-Y MCP Service
MCP for managing courses via HTTP API at oa-y.com.
Integration as MCP Server
This service supports two transport protocols for MCP integration: STDIO and StreamableHTTP.
Mode 1: STDIO (Local/Command Line)
For local integration with Cursor, Claude Desktop, or other MCP clients:
{
"mcpServers": {
"oa-y-mcp-service": {
"command": "npx",
"args": ["-y", "github:AdminRHS/oa-y-mcp-service"],
"env": {
"APP_ENV": "prod",
"API_TOKEN": "your_token",
"API_TOKEN_LIBS": "your_libs_token"
}
}
}
}
Mode 2: StreamableHTTP (Remote/HTTP)
For remote integration via StreamableHTTP:
{
"mcpServers": {
"oa-y-remote": {
"url": "http://your-server:3000/mcp?API_TOKEN=your_token&API_TOKEN_LIBS=your_libs_token&APP_ENV=prod"
}
}
}
When to use each transport:
- STDIO (stdin/stdout, Desktop‑first): Ideal for Desktop apps and local IDE integrations (Cursor, Claude Desktop).
- StreamableHTTP (/mcp, Browser/Agents‑first): Best for AI agents and browser/cloud clients (including proxies/tunnels).
API_TOKEN
How to get your API_TOKEN:
- Go to https://oa-y.com and log in as an admin.
- Open the Admin Panel and go to the API Tokens tab.
- Click Create Token, enter a name, and create the token.
- Copy the generated token and use it as the
API_TOKENenvironment variable.
API_TOKEN_LIBS
How to get your API_TOKEN_LIBS:
- Go to https://libs.anyemp.com and log in as an admin.
- Open the Admin Panel and go to the API Tokens tab.
- Click Create Token, enter a name (e.g., "Libs API"), and create the token.
- Copy the generated token and use it as the
API_TOKEN_LIBSenvironment variable.
APP_ENV
Environment setting:
prod- Production environment (default, uses oa-y.com and libs.anyemp.com)dev- Development/testing (uses lrn.oa-y.com and libdev.anyemp.com)
Available MCP Tools
This section describes all available tools for managing courses, lessons, modules, tests, and professions.
Course Management
get_courses— get a list of courses (with filters and pagination, supports profession filtering)get_course— get a course by idcreate_course— create a course (requires module IDs from create_module)update_course— update a course (requires module IDs from create_module)
Lesson Management
get_lessons— get a list of lessonsget_lesson— get a lesson by idcreate_lesson— create a lesson (use this first to get lesson IDs)update_lesson— update a lesson
Module Management
get_modules— get a list of modulesget_module— get a module by idcreate_module— create a module (requires lesson IDs from create_lesson)update_module— update a module (requires lesson IDs from create_lesson)
Test Management
get_tests— get a list of testsget_test— get a test by idcreate_test— create a test (requires lesson ID from create_lesson, tests are attached to lessons)update_test— update a test (requires lesson ID from create_lesson, tests are attached to lessons)
Profession Management
get_professions— get all professions (returns array with name and ID)get_skills— get all skills (returns array with name and ID)get_tools— get all tools (returns array with name and ID)
Creation Order
IMPORTANT: Follow the correct sequential creation order for courses, modules, lessons, and tests.
Sequential workflow:
-
CREATE COURSE:
- Use
create_courseto create the course structure - Can start with empty modules array, will be updated later
- Use
-
CREATE MODULE (at least one module required):
- Use
create_moduleto create a module - Can start with empty lessons array
- Get module ID from the response
- Use
-
CREATE FIRST LESSON (at least one lesson per module required):
- Use
create_lessonto create a lesson - Get lesson ID from the response
- Use
-
CREATE TEST FOR LESSON (optional):
- Use
create_testwith the lesson ID to attach test to this lesson - IMPORTANT: Tests are attached to lessons, not modules
- Get test ID from the response
- Use
-
UPDATE LESSON WITH TEST (if test was created):
- Use
update_lessonto add test IDs to the lesson's tests array
- Use
-
CREATE NEXT LESSON (repeat steps 3-5):
- Create another lesson for the same module
- Create tests for it
- Update lesson with test IDs
- Repeat until all lessons for this module are created
-
UPDATE MODULE WITH ALL LESSON IDS:
- Use
update_moduleto add all created lesson IDs to the module - Example:
lessons: ["lesson_id_1", "lesson_id_2", "lesson_id_3"]
- Use
-
CREATE NEXT MODULE (repeat steps 2-7):
- Create next module
- Create lessons for it
- Create tests for lessons
- Update lessons and module
- Repeat until all modules are created
-
UPDATE COURSE WITH ALL MODULE IDS:
- Use
update_courseto add all module IDs with their order - Example:
modules: [{ module: "module_id_1", order: 1 }, { module: "module_id_2", order: 2 }]
- Use
Required structure:
- Course must contain at least one module
- Module must contain at least one lesson
- Tests are optional but attached to lessons (not modules)
- Each module has ordered lessons
- Each course has ordered modules
Data flow:
Course
└─ Module 1 (order: 1)
├─ Lesson 1
│ └─ Test 1 (optional)
├─ Lesson 2
│ └─ Test 2 (optional)
└─ ...
└─ Module 2 (order: 2)
├─ Lesson 1
└─ ...
Example Requests
Get Courses:
{
"name": "get_courses",
"arguments": { "page": 1, "limit": 10 }
}
Get Courses by Professions:
{
"name": "get_courses",
"arguments": {
"professions": [68, 69],
"difficulty": "beginner"
}
}
Create Lesson (first):
{
"name": "create_lesson",
"arguments": {
"title": "Lesson Title",
"description": "Lesson description (optional)",
"type": "text",
"contentType": "standard",
"content": "Lesson content here",
"image": "https://example.com/lesson-image.jpg",
"duration": 30,
"professions": [],
"skills": [],
"tests": []
}
}
Create Module (with lesson IDs):
{
"name": "create_module",
"arguments": {
"title": "Module Title",
"content": "Module description (plain text)",
"description": "Optional detailed description",
"videoUrl": "https://example.com/video.mp4",
"previewImage": "https://example.com/preview.jpg",
"lessons": ["lesson_id_from_create_lesson"]
}
}
Note: Modules don't contain tests directly. Tests are attached to lessons.
Create Course (with module IDs):
{
"name": "create_course",
"arguments": {
"title": "Course Title",
"description": "Course description",
"difficulty": "beginner",
"modules": [
{
"module": "module_id_from_create_module",
"order": 1
}
],
"professions": [],
"image": "",
"duration": 60
}
}
Get Professions:
{
"name": "get_professions",
"arguments": {}
}
Get Skills:
{
"name": "get_skills",
"arguments": {}
}
Get Tools:
{
"name": "get_tools",
"arguments": {}
}
Create Test (with lesson ID):
{
"name": "create_test",
"arguments": {
"title": "Test Title",
"description": "Test description",
"lesson": "lesson_id_from_create_lesson",
"questions": [
{
"question": "What is HTML?",
"type": "single-choice",
"options": [
{ "text": "HyperText Markup Language", "isCorrect": true },
{ "text": "High Tech Modern Language", "isCorrect": false }
],
"points": 10
}
],
"passingScore": 70,
"timeLimit": 30
}
}
IMPORTANT: Tests are attached to lessons, not modules. Use lesson ID from create_lesson.
Update Course (with module IDs):
{
"name": "update_course",
"arguments": {
"courseId": "course_id_here",
"title": "Updated Course Title",
"description": "Updated course description",
"difficulty": "intermediate",
"modules": [
{
"module": "existing_module_id",
"order": 1
},
{
"module": "new_module_id_from_create_module",
"order": 2
}
]
}
}
Course Filtering by Professions
The get_courses tool supports filtering courses by profession IDs:
Workflow:
- Call
get_professionsto get all available professions with their IDs - Use profession IDs in
get_courseswith theprofessionsparameter
Parameters:
professions- Array of profession IDs (numbers)difficulty- Filter by difficulty: "beginner", "intermediate", "advanced"search- Search by course name or descriptionpage- Page number for paginationlimit- Number of courses per pageall- Get all courses without pagination
Testing
This section describes how to test the MCP service in different modes.
Testing Mode 1: STDIO (Local/Command Line)
Prerequisites:
- Node.js installed
- API tokens configured (see API_TOKEN and API_TOKEN_LIBS sections)
Steps:
-
Install dependencies:
npm install -
Build the bundled version:
npm run buildThis creates
oa-y-mcp-service.cjsfile that will be used by MCP clients. -
Configure your MCP client (Cursor/Claude Desktop):
Add to your MCP settings file:
{ "mcpServers": { "oa-y-local": { "command": "node", "args": ["c:/Projects/RH/oa-y-mcp-service/oa-y-mcp-service.cjs"], "env": { "APP_ENV": "prod", "API_TOKEN": "your_token", "API_TOKEN_LIBS": "your_libs_token" } } } } -
Restart your MCP client (Cursor/Claude Desktop)
-
Test the tools:
- Try calling
get_professionsto verify connection - Try creating a lesson with
create_lesson - Verify that all tools are available and working
- Try calling
For development/debugging:
npm run dev # Run in STDIO mode
npm run dev:inspect # Run with Node Inspector
Testing Mode 2: StreamableHTTP (Remote/HTTP)
Prerequisites:
- Node.js installed
- API tokens configured (see API_TOKEN and API_TOKEN_LIBS sections)
Steps:
-
Install dependencies:
npm install -
Start the HTTP server:
npm start # or npm run http -
Test health endpoint:
curl http://localhost:3000/health -
Configure your MCP client (Cursor/Claude Desktop):
Add to your MCP settings file:
{ "mcpServers": { "oa-y-http": { "url": "http://localhost:3000/mcp?API_TOKEN=your_token&API_TOKEN_LIBS=your_libs_token&APP_ENV=prod" } } } -
Restart your MCP client (Cursor/Claude Desktop)
-
Test the tools:
- Try calling
get_professionsto verify connection - Try creating a lesson with
create_lesson - Verify that all tools are available and working
- Try calling
For development/debugging:
npm run http:inspect # Run HTTP server with Node Inspector
Available HTTP endpoints:
GET /mcp— StreamableHTTP handshake/streamPOST /mcp— MCP protocol endpointGET /health— health checkGET /— service information
Testing with public URL (localtunnel):
For testing with remote access:
-
Install localtunnel:
npm install -g localtunnel -
Start your local server:
npm start -
Create a public tunnel:
lt --port 3000 --local-host localhost -
Use the provided URL in your MCP client:
{ "mcpServers": { "oa-y-remote": { "url": "https://random-subdomain.loca.lt/mcp?API_TOKEN=your_token&API_TOKEN_LIBS=your_libs_token&APP_ENV=prod" } } }
Deployment
This section describes how to deploy the MCP service for production use.
Deployment Mode 1: STDIO (NPM Package via GitHub)
This mode allows users to install your MCP service directly from GitHub using npx.
Requirements:
- Repository pushed to GitHub
- Built
oa-y-mcp-service.cjsfile committed to repository
Deployment Steps:
-
Build the bundled version:
npm run buildThis creates
oa-y-mcp-service.cjs— the bundled file that includes all dependencies. -
Commit and push to GitHub:
git add oa-y-mcp-service.cjs git commit -m "Build MCP service for distribution" git push origin main -
Users can now install via npx:
{ "mcpServers": { "oa-y-mcp-service": { "command": "npx", "args": ["github:AdminRHS/oa-y-mcp-service"], "env": { "APP_ENV": "prod", "API_TOKEN": "user_token", "API_TOKEN_LIBS": "user_libs_token" } } } }
Important:
- Always build before pushing:
npm run build - The built file
oa-y-mcp-service.cjsmust be committed to the repository - Users will download and run this file via
npx
Deployment Mode 2: StreamableHTTP (Docker on Server)
This mode deploys the MCP service as an HTTP server using Docker.
Requirements:
- Docker and Docker Compose installed on server
- Server with public IP or domain name
Deployment Steps:
-
On your server, clone the repository:
git clone https://github.com/AdminRHS/oa-y-mcp-service.git cd oa-y-mcp-service -
Create
.envfile (optional, for custom port):PORT=3000 -
Start the service with Docker Compose:
docker-compose up -d -
Verify the service is running:
curl http://localhost:3000/health -
Users can now connect via HTTP:
{ "mcpServers": { "oa-y-remote": { "url": "http://your-server-ip:3000/mcp?API_TOKEN=user_token&API_TOKEN_LIBS=user_libs_token&APP_ENV=prod" } } }
Docker Compose Configuration:
The service uses docker-compose.yml and Dockerfile:
- Builds image from Node.js Alpine
- Installs dependencies
- Exposes port 3000 (configurable via
.env) - Auto-restarts on failure
Updating the Deployment:
To update the service on the server:
git pull origin main
docker-compose down
docker-compose up -d --build
Monitoring:
View logs:
docker-compose logs -f
Check container status:
docker-compose ps
Production Recommendations:
- Use a reverse proxy (nginx/traefik) for HTTPS
- Set up proper firewall rules
- Use environment-specific API tokens
- Configure monitoring and alerts
- Set up automated backups
Response Format
All responses follow the MCP (Model Context Protocol) JSON-RPC 2.0 format. See MCP documentation for details.
Available Scripts
npm run dev- Run STDIO mode (local development)npm run dev:inspect- Run STDIO mode with Inspectornpm run http- Run HTTP server modenpm run http:inspect- Run HTTP server with Inspectornpm start- Start HTTP server (default)npm run build- Build bundled version (oa-y-mcp-service.cjs)
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.