Globalping MCP Server

<p align="center"> <img src="https://raw.githubusercontent.com/jsdelivr/globalping-media/refs/heads/master/logo/full_colored_dark.svg" alt="Globalping Logo" width="180"/> </p>

<p align="center"> <b>Enable AI models to interact with a global network measurement platform through natural language. Give network access to any LLM.</b> </p>

<p align="center"> <a href="https://github.com/modelcontextprotocol/modelcontextprotocol"> <img src="https://img.shields.io/badge/MCP-compatible-brightgreen.svg" alt="MCP Compatible"> </a> </p>

What is Globalping?

Globalping is a free, public API that provides access to a globally distributed network of probes for monitoring, debugging, and benchmarking internet infrastructure. With Globalping, you can run network tests (ping, traceroute, DNS, MTR, HTTP) from thousands of locations worldwide.

What is the Globalping MCP Server?

The Globalping MCP Server implements the Model Context Protocol (MCP), allowing AI models like OpenAI's GPT and Anthropic's Claude to interact with Globalping's network measurement capabilities through natural language.

It also supports oAuth authentication, which offers a secure way to interact with our API and benefits from higher rate limits associated with your account.

Key Features

• 🌐 Global Network Access: Run measurements from thousands of probes worldwide
• 🤖 AI-Friendly Interface: Any LLM will easily parse the data and run new measurements as needed
• 📊 Comprehensive Measurements: Support for ping, traceroute, DNS, MTR, and HTTP tests
• 🔍 Smart Context Handling: Provides detailed parameter descriptions for AI clients to intelligently select measurement types and options
• 🔄 Comparative Analysis: Allows to compare network performance between different targets
• 🔑 oAuth Support: Use your own Globalping account for higher rate limits

Installation

The remote MCP server is available under this endpoint https://mcp.globalping.dev/sse

You can integrate our Globalping MCP server with various AI tools that support the Model Context Protocol.

Here are instructions for the top 3 most popular tools:

Claude Desktop App

Add to your Claude Desktop configuration file (located at %APPDATA%\Claude\config.json on Windows or ~/Library/Application Support/Claude/config.json on macOS):

{
    "mcpServers": {
        "globalping": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.globalping.dev/sse"
            ]
        }
    }
}

Anthropic Claude API (via Console)

When creating a Claude Assistant in the Anthropic Console:

1. Go to console.anthropic.com
2. Navigate to the Assistants section
3. Create a new Assistant or edit an existing one
4. In the Tools section, select "Add custom tool"
5. Enter the following details:
   • Tool Name: Globalping
   • Description: Run network tests from locations worldwide
   • Tool URL: https://mcp.globalping.dev/sse

Cursor

To add the Globalping MCP server to Cursor:

1. Open Cursor settings
2. Navigate to the AI tab
3. Scroll down to find "Model Context Protocol"
4. Click "Add MCP Server"
5. Enter:
   • Name: Globalping
   • URL: https://mcp.globalping.dev/sse
   • Check "Enabled"
6. Click "Save"

Connecting AI Assistants

This MCP server can be used with any MCP-compatible AI assistant, including:

• Claude Desktop
• Anthropic Assistants
• Cursor
• Windsurf
• Any custom implementation of the MCP protocol

See the MCP documentation for details on connecting clients to this server.

Available Tools

• ping - Perform a ping test to a target
• traceroute - Perform a traceroute test to a target
• dns - Perform a DNS lookup for a domain
• mtr - Perform an MTR (My Traceroute) test to a target
• http - Perform an HTTP request to a URL
• locations - List all available Globalping probe locations
• limits - Show your current rate limits for the Globalping API
• getMeasurement - Retrieve a previously run measurement by ID
• compareLocations - Guide on how to run comparison measurements
• help - Show a help message with documentation on available tools

Usage Examples

Once connected to an AI model through a compatible MCP client, you can interact with Globalping using natural language:

Ping google.com from 3 locations in Europe

Run a traceroute to github.com from Japan and compare with traceroute from the US

Check the DNS resolution of example.com using Google DNS (8.8.8.8)

Is jsdelivr.com reachable from China? Test with both ping and HTTP

What's the average response time for cloudflare.com across different continents?

Location Specification

Locations can be specified using the "magic" field, which supports various formats:

• Continent codes: "EU", "NA", "AS", etc.
• Country codes: "US", "DE", "JP", etc.
• City names: "London", "Tokyo", "New York", etc.
• Network names: "Cloudflare", "Google", etc.
• ASN numbers: "AS13335", "AS15169", etc.
• Cloud provider regions: "aws-us-east-1", "gcp-us-central1", etc.

You can also combine these with a plus sign for more specific targeting: "London+UK", "Cloudflare+US", etc.

Development

The codebase is organized into modules:

• src/index.ts - Main entry point and MCP agent definition
• src/globalping/types.ts - TypeScript interfaces for the Globalping API
• src/globalping/api.ts - API wrapper functions for Globalping
• src/globalping/tools.ts - MCP tool implementations
• src/utils.ts - Helper utilities for rendering the web UI

Add Globalping credentials

Add Globalping OAuth credentials:

• npx wrangler secret put GLOBALPING_CLIENT_ID
• npx wrangler secret put GLOBALPING_CLIENT_SECRET

KV storage

Used for OAuthProvider docs https://github.com/cloudflare/workers-oauth-provider

• create a KV namespace and copy ID
• binding for it must be OAUTH_KV
• configure kv_namespaces in the wrangler.jsonc file