edhijlu/3gpp-mcp-server

3GPP MCP Server V3.0.0 - Direct Specification Access

Transform your AI assistant into a 3GPP specification expert with direct access to TSpec-LLM's 535M word dataset!

What This Does

Before: Ask AI about 3GPP specifications - Get generic responses based on training data After: Ask AI + 3GPP MCP Server V3.0.0 - Get direct access to current specification content with structured, agent-ready responses

Revolutionary V3.0.0 Architecture

V3.0.0 represents the True MCP approach - lightweight API bridge providing direct specification data:

Agent Query → MCP Tools → External APIs → Real Specification Data

Key Benefits:

• True MCP Architecture - Lightweight API bridge (~10MB vs 15GB+)
• Sub-500ms responses - Intelligent caching with external API integration
• Agent-optimized - Structured JSON responses for AI agent consumption
• Real specification data - Direct access to TSpec-LLM's 535M word dataset
• External API integration - Hugging Face + 3GPP.org APIs
• Infinite scalability - Stateless API calls, no local storage limits

Quick Start (30 Seconds!)

Direct MCP Setup (Recommended)

Claude Desktop users:

claude mcp add 3gpp-server npx 3gpp-mcp-charging@latest serve

For other MCP clients: Add this to your MCP configuration:

{
  "mcpServers": {
    "3gpp-server": {
      "command": "npx",
      "args": ["3gpp-mcp-charging@latest", "serve"],
      "description": "3GPP MCP Server - Direct access to TSpec-LLM and 3GPP specifications",
      "env": {
        "HUGGINGFACE_TOKEN": "optional-for-enhanced-access"
      }
    }
  }
}

Alternative: Auto-Configuration

# One-command installation with auto-configuration
npx 3gpp-mcp-charging@latest init

# Client-specific installation
npx 3gpp-mcp-charging@latest init --client claude
npx 3gpp-mcp-charging@latest init --client vscode
npx 3gpp-mcp-charging@latest init --client cursor

Test It Works

Ask your AI assistant: "Search for 5G CHF implementation requirements in TS 32.290"

You should get structured specification content with implementation guidance, dependencies, and testing considerations!

Available Tools (V3.0.0)

Example Queries

Direct Specification Search:

"Find charging procedures in 5G service-based architecture"
→ Returns: TS 32.290 excerpts, CHF implementation details, Nchf interface specifications

Implementation Requirements:

"Extract implementation requirements for converged charging in Release 17"
→ Returns: Technical requirements, dependencies, testing considerations, compliance notes

Specification Comparison:

"Compare charging evolution from TS 32.240 to TS 32.290"
→ Returns: Evolution timeline, migration analysis, implementation impact assessment

What You Get

Direct Specification Content

• Real-time access to TSpec-LLM's comprehensive 3GPP dataset
• Structured content excerpts with relevance scoring
• Official specification metadata integration

Agent-Ready Responses

• JSON-formatted responses optimized for AI agent consumption
• Consistent schema across all tool responses
• Rich metadata embedded in all responses

Implementation Intelligence

• Technical requirements extraction from specifications
• Dependency analysis and implementation guidance
• Testing considerations and compliance mapping

Performance Benefits

• <500ms cached response times
• <2s fresh API call responses
• <10MB memory footprint (stateless design)
• Unlimited concurrent users (external API scaling)

Architecture

Core Components

External API Integration Layer

• TSpec-LLM Client: Direct integration with TSpec-LLM dataset via Hugging Face APIs
• 3GPP API Client: Integration with official 3GPP.org APIs for metadata
• API Manager: Unified orchestration layer for all external APIs

MCP Tool Layer

• search_specifications.ts: Direct specification search implementation
• get_specification_details.ts: Comprehensive specification details
• compare_specifications.ts: Multi-specification comparison
• find_implementation_requirements.ts: Requirements extraction

Caching & Performance

• NodeCache: Intelligent API response caching
• Rate Limiting: Respectful external API usage
• Error Handling: Robust API integration with fallbacks

Project Structure

3gpp-mcp-server-v2/
├── src/                          # V3.0.0 source code
│   ├── api/                      # External API integration layer
│   │   ├── tspec-llm-client.ts   # TSpec-LLM Hugging Face client
│   │   ├── tgpp-api-client.ts    # 3GPP.org official API client
│   │   ├── api-manager.ts        # Unified API orchestration
│   │   └── index.ts              # API exports
│   ├── tools/                    # MCP tool implementations
│   │   ├── search-specifications.ts           # Direct specification search
│   │   ├── get-specification-details.ts       # Comprehensive spec details
│   │   ├── compare-specifications.ts          # Multi-spec comparison
│   │   ├── find-implementation-requirements.ts # Requirements extraction
│   │   └── index.ts              # Tool exports
│   ├── types/                    # TypeScript interfaces
│   └── index.ts                  # MCP server implementation
├── bin/                          # CLI installation tools
├── docs/                         # Documentation
├── tests/                        # Test suite
└── package.json                  # NPM package configuration

Requirements

• Node.js 18+ - Download from nodejs.org
• MCP-compatible AI assistant (Claude Desktop, VS Code, Cursor, or others)
• Internet connection - For external API access
• Optional: Hugging Face token - For enhanced API access

Installation Options

Option 1: Direct MCP Configuration (Recommended)

No local installation needed! Server runs directly from NPM.

Option 2: Development Setup

# Clone and setup for development
git clone <repository-url>
cd 3gpp-mcp-server/3gpp-mcp-server-v2
npm install
npm run build
npm run start

Option 3: Auto-Configuration

npx 3gpp-mcp-charging@latest init

Environment Variables

# Optional: Enhanced API access
export HUGGINGFACE_TOKEN="your-huggingface-token"

# Optional: Custom cache settings
export CACHE_TIMEOUT="3600"  # seconds
export ENABLE_CACHING="true"

Version Evolution

Development

Available Scripts

npm run build      # Build TypeScript
npm run dev        # Development with watch
npm run start      # Run the server
npm run test       # Run tests
npm run lint       # Lint code
npm run clean      # Clean build artifacts

Adding New Tools

1. Create tool class in src/tools/
2. Define tool schema with input/output types
3. Implement execute() method with API integration
4. Export tool and register in src/index.ts

API Integration

• Extend TSpecLLMClient for new TSpec-LLM capabilities
• Extend TGPPApiClient for additional 3GPP.org endpoints
• Add orchestration methods to APIManager

Contributing

Contributions welcome! Please focus on:

• API integration improvements
• Performance optimizations
• New MCP tool implementations
• Documentation enhancements

License

BSD-3-Clause License - see LICENSE file for details.

Acknowledgments

Research Foundation

This project's V3.0.0 architecture was fundamentally inspired by the TSpec-LLM research:

TSpec-LLM: A Large Language Model for 3GPP Specifications

• Paper: https://arxiv.org/abs/2406.01768
• Authors: Rasoul Nikbakht, et al.
• Dataset: TSpec-LLM on Hugging Face

Originally planned as a document reference MCP, discovery of the TSpec-LLM research paper fundamentally changed our approach. The paper's demonstration of significant accuracy improvements (25+ percentage points) through direct LLM access to 3GPP specifications convinced us to pivot from document hosting to external API integration with their comprehensive 535M word dataset.

Technical Foundation

• Built using the Model Context Protocol SDK
• Integrates with TSpec-LLM dataset
• Supports 3GPP specifications from 3GPP.org

V3.0.0: True MCP architecture providing direct specification access through external API integration.