Enables network performance analysis and diagnostics to Google services through multiple Looking Glass vantage points, as demonstrated in the CDN performance analysis example using Google's DNS service (8.8.8.8).
Looking-Glass-MCP
The first Looking Glass Model Context Protocol (MCP) server! 🎉
Overview
Looking-Glass-MCP is a revolutionary MCP server that provides network probing capabilities through Looking Glass (LG) vantage points. This tool allows you to perform network diagnostics and measurements from multiple global locations using a simple, standardized interface.
Features
- Multi-VP Probing: Execute network commands from multiple Looking Glass vantage points simultaneously
- Auto VP Selection: Automatically select the optimal number of vantage points for your measurements
- Comprehensive Commands: Support for ping, BGP route lookups, and traceroute operations
- Global Coverage: Access to Looking Glass servers worldwide
- Async Operations: Built with async/await for efficient concurrent operations
- Error Handling: Robust error handling and timeout management
Available Tools
lg_probing_user_defined
Send probing commands to a target IP using a specific list of LG vantage points.
Parameters:
vp_id_list
: List of Looking Glass VP identifierscmd
: Command type (ping
,show ip bgp
,traceroute
)target_ip
: Destination IP address for probing
lg_probing_auto_select
Send probing commands using automatically selected vantage points.
Parameters:
vp_num
: Number of vantage points to usecmd
: Command type (ping
,bgp
,traceroute
)target_ip
: Destination IP address for probing
list_all_lgs
Retrieve information about all available Looking Glass vantage points.
Requirements
- Python 3.13+
- httpx >= 0.28.1
- mcp[cli] >= 1.9.4
Installation
Usage Example: CDN Performance Analysis
This example demonstrates how to use Looking-Glass-MCP for CDN performance optimization by analyzing network performance to Google's DNS service (8.8.8.8) from multiple global locations.
Step 1: List Available Vantage Points
Step 2: Select Global Vantage Points
We selected 5 diverse global locations for comprehensive analysis:
- US (Seattle): VP ID 71 - North America
- Switzerland: VP ID 164 - Europe
- Singapore: VP ID 62 - Asia-Pacific
- Australia (Sydney): VP ID 125 - Oceania
- Brazil (Campo Grande): VP ID 108 - South America
Step 3: Execute Network Probing
Step 4: LLM-Generated Analysis Results
📊 Example Output: The following analysis was automatically generated by an LLM using the Looking-Glass-MCP tool results. This demonstrates how AI can transform raw network data into actionable business insights.
🌍 Global Network Performance Summary
Location | Country | Latency (avg) | Packet Loss | Performance Rating |
---|---|---|---|---|
Seattle, US | US | ~1-4ms | 0% | ⭐⭐⭐⭐⭐ Excellent |
Switzerland | CH | ~1ms | 0% | ⭐⭐⭐⭐⭐ Excellent |
Singapore | SG | ~2.1ms | 0% | ⭐⭐⭐⭐⭐ Excellent |
Sydney, Australia | AU | ~0.54ms | 0% | ⭐⭐⭐⭐⭐ Outstanding |
Campo Grande, Brazil | BR | ~19.8ms | 0% | ⭐⭐⭐ Good |
🔍 Key Findings
Best Performance:
- Australia (Sydney): Exceptionally low latency (~0.54ms) - direct Google peering
- Switzerland & US: Sub-millisecond to low single-digit latency
Routing Analysis:
- Australia: 6 hops, direct peering with Google infrastructure
- Singapore: 4 hops, excellent Google edge presence
- Switzerland: 4 hops, optimal European routing
- Brazil: 15+ hops, complex ISP routing causing higher latency
BGP Intelligence:
- All locations show AS15169 (Google) as origin
- Multiple path redundancy visible
- Local peering arrangements in major markets
🎯 CDN Optimization Recommendations
Immediate Actions:
- Prioritize APAC: Australia and Singapore show excellent performance
- European Expansion: Switzerland performance suggests good connectivity
- Brazil Improvement: Higher latency indicates need for local presence
Strategic Recommendations:
- Multi-CDN Strategy: Deploy edge servers in Sydney, Singapore, and Europe
- Peering Optimization: Establish direct peering with major ISPs in Brazil
- Performance Monitoring: Use these 5 locations as baseline monitoring points
Expected Impact:
- Australia/Singapore: Maintain sub-2ms response times
- Europe: Target sub-5ms response times
- Brazil: Improve from 20ms to <10ms with local presence
💡 Key Insight: This example shows how Looking-Glass-MCP enables AI assistants to automatically analyze complex network data and provide actionable business recommendations - transforming raw technical metrics into strategic insights.
Real-World Applications
This Looking Glass MCP tool is perfect for:
- CDN Performance Optimization: Analyze global performance patterns
- Network Troubleshooting: Identify routing issues from multiple perspectives
- DDoS Detection: Monitor traffic patterns across vantage points
- Competitive Analysis: Benchmark against competitor infrastructure
- SLA Monitoring: Validate service level agreements globally
- Research: Academic studies on internet topology and performance
Getting Started
- Install dependencies
- Configure your MCP client to use Looking-Glass-MCP
- Start analyzing global network performance!
The power of Looking Glass combined with MCP's standardized interface makes network analysis accessible and actionable for any application requiring global network intelligence.
This server cannot be installed
A Model Context Protocol server that provides network probing capabilities through Looking Glass vantage points, allowing users to perform global network diagnostics like ping, BGP route lookups, and traceroute operations from multiple locations worldwide.
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