3GPP MCP Server
Enables AI assistants to access and search 3GPP telecommunications specifications through direct integration with the TSpec-LLM dataset. Provides real-time specification content, implementation requirements, and multi-spec comparisons for 3GPP standards development.
README
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)
| Tool | Purpose | Input | Output |
|---|---|---|---|
search_specifications |
Direct TSpec-LLM search | Query + filters | Structured spec results + relevance scores |
get_specification_details |
Comprehensive spec details | Specification ID | Full metadata + implementation guidance |
compare_specifications |
Multi-spec comparison | Array of spec IDs | Comparison matrix + migration analysis |
find_implementation_requirements |
Requirements extraction | Spec scope + focus | Technical requirements + testing guidance |
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
| Version | Approach | Storage | Architecture |
|---|---|---|---|
| V1 | Data Hosting | 15GB+ local dataset | Heavy, non-MCP compliant |
| V2 | Guidance Templates | <100MB knowledge base | Lightweight, guidance-only |
| V3.0.0 | Direct Data Access | <10MB (stateless) | True MCP API bridge |
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
- Create tool class in
src/tools/ - Define tool schema with input/output types
- Implement
execute()method with API integration - Export tool and register in
src/index.ts
API Integration
- Extend
TSpecLLMClientfor new TSpec-LLM capabilities - Extend
TGPPApiClientfor 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.
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