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Looking-Glass-MCP

by Jackie-shi

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 identifiers
  • cmd: 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 use
  • cmd: 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

pip install -r requirements.txt

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

# Get all available Looking Glass vantage points result = await list_all_lgs()

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

# Run ping tests from 5 global locations ping_results = await lg_probing_user_defined( vp_id_list=["71", "164", "62", "125", "108"], cmd="ping", target_ip="8.8.8.8" ) # Run traceroute analysis traceroute_results = await lg_probing_user_defined( vp_id_list=["71", "164", "62", "125", "108"], cmd="traceroute", target_ip="8.8.8.8" ) # Analyze BGP routing information bgp_results = await lg_probing_user_defined( vp_id_list=["71", "164", "62", "125", "108"], cmd="bgp", target_ip="8.8.8.8" )

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
LocationCountryLatency (avg)Packet LossPerformance Rating
Seattle, USUS~1-4ms0%⭐⭐⭐⭐⭐ Excellent
SwitzerlandCH~1ms0%⭐⭐⭐⭐⭐ Excellent
SingaporeSG~2.1ms0%⭐⭐⭐⭐⭐ Excellent
Sydney, AustraliaAU~0.54ms0%⭐⭐⭐⭐⭐ Outstanding
Campo Grande, BrazilBR~19.8ms0%⭐⭐⭐ 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:

  1. Prioritize APAC: Australia and Singapore show excellent performance
  2. European Expansion: Switzerland performance suggests good connectivity
  3. Brazil Improvement: Higher latency indicates need for local presence

Strategic Recommendations:

  1. Multi-CDN Strategy: Deploy edge servers in Sydney, Singapore, and Europe
  2. Peering Optimization: Establish direct peering with major ISPs in Brazil
  3. 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

  1. Install dependencies
  2. Configure your MCP client to use Looking-Glass-MCP
  3. 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.

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security - not tested
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license - not found
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quality - not tested

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.

  1. Overview
    1. Features
      1. Available Tools
        1. lg_probing_user_defined
        2. lg_probing_auto_select
        3. list_all_lgs
      2. Requirements
        1. Installation
          1. Usage Example: CDN Performance Analysis
            1. Step 1: List Available Vantage Points
            2. Step 2: Select Global Vantage Points
            3. Step 3: Execute Network Probing
            4. Step 4: LLM-Generated Analysis Results
            5. Real-World Applications
          2. Getting Started

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