Learning Hour Generator▌
by sdiamante13
Learning Hour Generator creates 60-minute technical practice sessions for dev teams using GitHub analysis and the 4C Lea
Generates structured 60-minute technical practice sessions for software development teams using the 4C Learning Model by analyzing GitHub repositories for code smells and creating contextual learning content with Miro board layouts.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Technical coaches facilitating team learning sessions
- / Team leads improving their team's technical practices
- / Developers organizing coding dojos or practice sessions
capabilities
- / Generate Learning Hour session plans with the 4C model
- / Analyze GitHub repositories for code smells and issues
- / Create interactive Miro boards for team sessions
- / Generate code examples and practice exercises
- / Structure deliberate practice activities for teams
what it does
Generates structured 60-minute technical practice sessions for software development teams using the 4C Learning Model. Analyzes GitHub repositories for code smells and creates contextual learning content with optional Miro board layouts.
about
Learning Hour Generator is a community-built MCP server published by sdiamante13 that provides AI assistants with tools and capabilities via the Model Context Protocol. Learning Hour Generator creates 60-minute technical practice sessions for dev teams using GitHub analysis and the 4C Lea It is categorized under ai ml, developer tools.
how to install
You can install Learning Hour Generator in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
MIT
Learning Hour Generator is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
learning-hour-mcp
Generate Learning Hour content for Technical Coaches using AI. Create structured practice sessions that help development teams master technical excellence through the 4C Learning Model.
What is this?
An MCP server that helps Technical Coaches run Learning Hours - structured 60-minute practice sessions where teams improve their coding skills through deliberate practice. It generates session plans, code examples, and can even create interactive Miro boards.
Who is this for?
- Technical Coaches facilitating team learning sessions
- Team Leads wanting to improve their team's technical practices
- Developers organizing coding dojos or practice sessions
Installation
Prerequisites
- Claude Desktop - Install the desktop app
- Anthropic API Key - Sign up and create a key ($5 free credit for new accounts)
Complete Setup
Choose your preferred editor:
Claude Desktop
Add to your Claude Desktop configuration:
{
"mcpServers": {
"learning-hour": {
"command": "npx",
"args": ["-y", "learning-hour-mcp"],
"env": {
"ANTHROPIC_API_KEY": "your-anthropic-key",
"MIRO_ACCESS_TOKEN": "your-miro-token-optional",
"GITHUB_TOKEN": "your-github-token-optional"
}
}
}
}
Configuration steps:
- Open Claude Desktop settings (cmd/ctrl + ,)
- Go to "Developer" → "Edit Config"
- Paste the configuration above
- Replace
your-anthropic-keywith your actual key - Save and restart Claude Desktop
VSCode
Add to your VSCode settings.json:
{
"mcp.servers": {
"learning-hour": {
"command": "npx",
"args": ["-y", "learning-hour-mcp"],
"env": {
"ANTHROPIC_API_KEY": "your-anthropic-key",
"MIRO_ACCESS_TOKEN": "your-miro-token-optional",
"GITHUB_TOKEN": "your-github-token-optional"
}
}
}
}
Configuration steps:
- Install the MCP VSCode Extension
- Open settings.json (Cmd/Ctrl+Shift+P → "Preferences: Open Settings (JSON)")
- Add the configuration above
- Replace tokens with your actual values
- Reload VSCode window (Cmd/Ctrl+Shift+P → "Developer: Reload Window")
Cursor
Add to your Cursor configuration:
{
"mcpServers": {
"learning-hour": {
"command": "npx",
"args": ["-y", "learning-hour-mcp"],
"env": {
"ANTHROPIC_API_KEY": "your-anthropic-key",
"MIRO_ACCESS_TOKEN": "your-miro-token-optional",
"GITHUB_TOKEN": "your-github-token-optional"
}
}
}
}
Configuration steps:
- Open Cursor settings (Cmd/Ctrl + ,)
- Click on "Features" → "Claude" → "Advanced"
- Add the MCP server configuration
- Replace tokens with your actual values
- Restart Cursor
Required: Only ANTHROPIC_API_KEY is required. The other tokens enable additional features.
Quick Start
After installation, try this in Claude:
"Use the learning hour tools to create a session about the Extract Method refactoring"
Claude will generate a complete 60-minute session plan with:
- Opening connection activity
- Concept introduction
- Hands-on coding exercise
- Reflection and commitment
Available Tools
generate_session
Generate a complete Learning Hour session plan with activities following the 4C model (Connect, Concept, Concrete, Conclusion).
{
"topic": "Feature Envy"
}
generate_code_example
Create before/after code examples for a specific topic.
{
"topic": "Extract Method",
"language": "typescript"
}
create_miro_board
Create a new Miro board or add frames to an existing board (requires MIRO_ACCESS_TOKEN).
{
"sessionContent": { /* from generate_session */ },
"existingBoardId": "optional-board-id" // If provided, adds frames to existing board
}
list_miro_boards
List all Miro boards accessible with your token (requires MIRO_ACCESS_TOKEN).
{
"limit": 50, // Optional, max 50
"cursor": "optional-pagination-cursor"
}
get_miro_board
Get details about a specific Miro board (requires MIRO_ACCESS_TOKEN).
{
"boardId": "board-id-to-get"
}
delete_miro_board
Delete a Miro board (requires MIRO_ACCESS_TOKEN). Use with caution!
{
"boardId": "board-id-to-delete",
"confirm": true // Required safety check
}
analyze_repository
Find real code examples in GitHub repositories (requires GITHUB_TOKEN).
analyze_tech_stack
Analyze a repository's technology stack to create team-specific content (requires GITHUB_TOKEN).
Optional Features
Enable Miro Board Creation
Transform your Learning Hour into a visual, interactive workshop board
Get a Miro token:
- Go to Miro Apps
- Create a new app (name it "Learning Hours")
- Copy the access token
- Add as
MIRO_ACCESS_TOKENin your config
Enable Repository Analysis
Find real code examples from your team's actual codebase
Create a GitHub Personal Access Token:
- Name: "Learning Hour MCP"
- Expiration: 90 days (recommended)
- Permissions:
repo(read access) - Add as
GITHUB_TOKENin your config
Learn More
- Diamante Technical Coaching - Refactor to Grow Newsletter
- SammanCoaching.org - Technical coaching resources and Learning Hour guides
- Learning Hours - Catalog of Learning Hour topics
- 4C Learning Model - Connect, Concept, Concrete, Conclusion
- Technical Coaching - Role and practices
Troubleshooting
"Tool not found" error: Make sure you restarted Claude Desktop after adding the configuration.
"Invalid API key": Check that you copied the entire key including any prefixes (sk-ant-...).
Miro board not creating: Check that your MIRO_ACCESS_TOKEN is valid and has board creation permissions.
Contributing
See CONTRIBUTING.md for development setup and guidelines.
License
MIT
FAQ
- What is the Learning Hour Generator MCP server?
- Learning Hour Generator is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for Learning Hour Generator?
- This profile displays 67 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Extended AI Capabilities
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Context Enhancement
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Workflow Automation
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
- ›Basic understanding of MCP architecture and capabilities
- ›Access credentials for integrated services (if required)
- ›Willingness to experiment and iterate on configuration
Time Estimate
15-60 minutes depending on server complexity
Installation Steps
- 1.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 7.Document successful patterns for reuse
Troubleshooting
- ⚠MCP server not loading: Check config syntax, verify installation
- ⚠Connection errors: Check network, firewall, credentials
- ⚠Feature not working: Read server docs, check required parameters
- ⚠Performance issues: Monitor resource usage, check for network latency
- ⚠Conflicts with other servers: Check port assignments, namespace collisions
Best Practices▌
✓ Do
- +Read server documentation thoroughly before setup
- +Start with simple use cases to validate functionality
- +Test in non-production environment first
- +Monitor resource usage and performance
- +Keep servers updated for bug fixes and new features
- +Document configuration for team members
- +Use environment variables for sensitive configuration
✗ Don't
- −Don't grant overly permissive access to MCP servers
- −Don't skip reading security considerations in docs
- −Don't expose sensitive data without proper controls
- −Don't run untrusted MCP servers without code review
- −Don't ignore error messages—investigate root cause
💡 Pro Tips
- ★Combine multiple MCP servers for powerful workflows
- ★Create custom MCP servers for your specific needs
- ★Share successful configurations with team
- ★Use MCP inspector for debugging
- ★Join MCP community for tips and troubleshooting
Technical Details▌
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
- Model Context Protocol (MCP)
- JSON-RPC 2.0
- stdio or HTTP transport
Compatibility
- Claude Desktop
- Cursor IDE
- Custom MCP clients
When to Use This▌
✓ Use When
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid When
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
Integration▌
- →Tool composition: Chain multiple MCP tools in workflows
- →Context augmentation: Provide AI with relevant external data
- →Action delegation: Let AI execute tasks on external systems
- →Bidirectional sync: Keep AI context and external systems in sync
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
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Ratings
4.5★★★★★67 reviews- ★★★★★Hana Reddy· Dec 28, 2024
Learning Hour Generator is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Mei Agarwal· Dec 20, 2024
Strong directory entry: Learning Hour Generator surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Noah Reddy· Dec 12, 2024
We wired Learning Hour Generator into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Hassan Menon· Dec 8, 2024
I recommend Learning Hour Generator for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Noah Sethi· Dec 4, 2024
We evaluated Learning Hour Generator against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Kwame Thomas· Dec 4, 2024
According to our notes, Learning Hour Generator benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Noah Malhotra· Nov 23, 2024
Useful MCP listing: Learning Hour Generator is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Noah Shah· Nov 23, 2024
We wired Learning Hour Generator into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Noah Sharma· Nov 19, 2024
Learning Hour Generator reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Olivia Ramirez· Nov 7, 2024
Strong directory entry: Learning Hour Generator surfaces stars and publisher context so we could sanity-check maintenance before adopting.
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