Roblox Documentation MCP Server

Roblox Documentation MCP Server

Enables AI agents to intelligently search and retrieve Roblox documentation through semantic search and vector embeddings, providing natural language access to complete Roblox Creator Documentation.

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🚀 Roblox Documentation MCP Server with RAG Support

TypeScript Model Context Protocol SDK MCP Spec Version Version License Status

MCP server with RAG support for intelligent Roblox documentation search and retrieval

This MCP server enables AI agents to intelligently search and retrieve Roblox documentation through semantic search and vector embeddings. It provides natural language access to the complete Roblox Creator Documentation.

🎯 What This Does

Enable AI agents to:

  • 🔍 Semantic Search: Find relevant documentation through natural language queries
  • 📚 API References: Get specific details about Roblox classes, methods, and properties
  • 🎓 Tutorial Discovery: Locate step-by-step guides and learning materials
  • 💡 Code Examples: Find relevant code snippets and demonstrations
  • 🏷️ Smart Filtering: Search by content type, difficulty, or topic

🏗️ Architecture

graph TD
    A[AI Agent] --> B[MCP Server]
    B --> C[RAG Service]
    C --> D[ChromaDB Vector Store]
    C --> E[OpenAI Embeddings]
    B --> F[Git Service]
    F --> G[Roblox/creator-docs Repository]
    B --> H[Content Processor]
    H --> I[Markdown Parser]
    H --> J[YAML Parser]

✨ Key Features

Feature Area Description Implementation
🔍 Semantic Search Natural language queries across all Roblox documentation ChromaDB + OpenAI embeddings
📖 Content Processing Processes markdown guides, tutorials, and YAML API references markdown-it + yaml parsers
🔄 Auto-Updates Keeps documentation current via git pull from official repository simple-git integration
🏷️ Smart Classification Automatically categorizes content (guides, tutorials, API references) Metadata extraction + classification
⚡ Performance Fast semantic search with caching and optimized vector storage Redis caching + ChromaDB
🔒 Production Ready Built on proven MCP template with comprehensive error handling Full TypeScript + Zod validation

🚀 Quick Start

Prerequisites

  • Node.js 20+
  • ChromaDB server (Docker recommended)
  • OpenAI API key

Installation

# Clone the repository
git clone https://github.com/christopher-buss/roblox-docs-mcp.git
cd roblox-docs-mcp

# Install dependencies
npm install

# Set up environment variables
cp .env.example .env
# Edit .env with your OpenAI API key and ChromaDB settings

# Start ChromaDB (using Docker)
docker run -p 8000:8000 chromadb/chroma

# Build the project
npm run build

Environment Configuration

Create a .env file with the following variables:

# OpenAI Configuration
OPENAI_API_KEY=your_openai_api_key

# ChromaDB Configuration
CHROMA_DB_URL=http://localhost:8000
CHROMA_DB_COLLECTION=roblox-docs

# Roblox Documentation
ROBLOX_DOCS_REPO_URL=https://github.com/Roblox/creator-docs.git
ROBLOX_DOCS_LOCAL_PATH=./data/roblox-docs
ROBLOX_DOCS_UPDATE_INTERVAL=24

# Embedding Configuration
EMBEDDING_MODEL=text-embedding-3-large
MAX_CHUNK_SIZE=1000
CHUNK_OVERLAP=200

# Optional Redis Cache
REDIS_URL=redis://localhost:6379

Running the Server

# Start MCP server (stdio transport)
npm run start:stdio

# Start MCP server (HTTP transport)
npm run start:http

# Update documentation repository
npm run docs:update

# Launch MCP inspector for debugging
npm run inspector

🛠️ Available MCP Tools

searchRobloxDocs

Purpose: Semantic search across all Roblox documentation
Input: Natural language query, optional filters
Output: Ranked list of relevant documentation with metadata

getRobloxApiReference

Purpose: Get specific API class/method documentation
Input: API name, class name, method name
Output: Detailed API documentation with examples

findRobloxTutorials

Purpose: Find step-by-step tutorials and guides
Input: Topic, difficulty level, tutorial type
Output: Curated list of tutorials with descriptions

getRobloxGuides

Purpose: Retrieve conceptual guides and explanations
Input: Topic area, content type
Output: Relevant guides with structured content

📁 Project Structure

src/
├── services/
│   ├── git-service/          # Git repository operations
│   ├── content-processor/    # Markdown/YAML processing
│   └── roblox-rag/          # RAG implementation
├── mcp-server/
│   ├── tools/               # MCP tools for documentation search
│   └── server.ts            # Main MCP server
├── config/                  # Configuration management
└── utils/                   # Production utilities

🔧 Development

Architecture Overview

This project extends the cyanheads/mcp-ts-template with Roblox-specific capabilities:

  • Git Service: Manages the Roblox creator-docs repository
  • Content Processor: Parses markdown and YAML files
  • RAG Service: Handles embeddings and semantic search
  • MCP Tools: Provides search and retrieval capabilities

Adding New Features

  1. New Tools: Follow the template pattern in src/mcp-server/tools/
  2. Content Processing: Extend processors in src/services/content-processor/
  3. RAG Enhancements: Modify search logic in src/services/roblox-rag/

Development Commands

npm run build          # Build TypeScript
npm run format         # Format code with Prettier
npm run docs:generate  # Generate TypeDoc documentation
npm run tree          # Generate project structure
npm run depcheck      # Check for unused dependencies

🧪 Testing

# Test individual components
npm run test:unit

# Test MCP tools end-to-end
npm run test:integration

# Test RAG functionality
npm run test:rag

📊 Performance

  • Search Latency: < 500ms for semantic queries
  • Memory Usage: < 2GB RAM for full documentation index
  • Document Processing: 100+ docs/minute ingestion rate
  • Cache Hit Rate: > 80% for repeated queries

🤝 Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Add tests if applicable
  5. Submit a pull request

📜 License

This project is licensed under the Apache License 2.0. See the LICENSE file for details.

🙏 Acknowledgments

📚 Documentation


Note: This project is currently in development. See DEVELOPMENT_PLAN.md for current status and implementation progress.

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