Globalping▌
by jsdelivr
Run a ping test worldwide with Globalping. Diagnose connectivity issues using Cloudflare Workers for accurate network tr
Provides global network diagnostics through Cloudflare Workers, enabling engineers to run tests like ping, traceroute, and HTTP requests from worldwide locations for troubleshooting connectivity issues and analyzing network performance.
github stars
★ 48
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Network engineers troubleshooting connectivity
- / DevOps teams monitoring global infrastructure
- / Developers testing CDN performance
- / IT teams debugging regional network issues
capabilities
- / Run ping tests from global probe locations
- / Perform traceroute analysis worldwide
- / Execute DNS lookups from multiple regions
- / Test HTTP requests from distributed locations
- / Compare network performance between targets
- / Access thousands of measurement probes globally
what it does
Runs network diagnostic tests (ping, traceroute, DNS, HTTP) from thousands of worldwide locations through Cloudflare Workers. Helps troubleshoot connectivity issues and analyze network performance globally.
about
Globalping is an official MCP server published by jsdelivr that provides AI assistants with tools and capabilities via the Model Context Protocol. Run a ping test worldwide with Globalping. Diagnose connectivity issues using Cloudflare Workers for accurate network tr It is categorized under developer tools.
how to install
You can install Globalping in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server supports remote connections over HTTP, so no local installation is required.
license
MIT
Globalping is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
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 two authentication methods: OAuth and API token authentication. Both methods offer a secure way to interact with our API and provide 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
- 🔑 Authentication Support: Use OAuth or API token with your Globalping account for higher rate limits
Installation
The remote MCP server is available under these endpoints:
- Streamable HTTP transport:
https://mcp.globalping.dev/mcp - SSE transport:
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:
Gemini CLI
To add the Globalping MCP server to Gemini CLI:
- Ensure you have the Gemini CLI installed.
- Run the following command:
gemini extensions install https://github.com/jsdelivr/globalping-mcp-server
This will automatically configure the server with OAuth authentication enabled. You will be prompted to log in when you first use the extension.
Note: If you prefer to use a Globalping API token (for higher rate limits or automation), you can manually add the server with the Authorization header instead of using the extension installer:
gemini mcp add globalping https://mcp.globalping.dev/mcp --header "Authorization: Bearer YOUR_TOKEN"
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):
[!note] Claude Desktop natively supports only stdio transport for local MCP servers. For remote MCP servers, use the
mcp-remotebridge.
{
"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:
- Go to console.anthropic.com
- Navigate to the Assistants section
- Create a new Assistant or edit an existing one
- In the Tools section, select "Add custom tool"
- Enter the following details:
- Tool Name:
Globalping - Description:
Run network tests from locations worldwide - Tool URL:
https://mcp.globalping.dev/mcp(Streamable HTTP transport) orhttps://mcp.globalping.dev/sse(SSE transport)
- Tool Name:
Cursor
To add the Globalping MCP server to Cursor:
- Open Cursor settings
- Navigate to the Tools & MCP tab
- Click on "+ New MCP server"
- This opens the
mcp.jsonconfig file, where you will need to add:
Streamable HTTP transport:
{
"mcpServers": {
"globalping": {
"url": "https://mcp.globalping.dev/mcp"
}
}
}
Legacy SSE transport:
{
"mcpServers": {
"globalping": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.globalping.dev/sse"
]
}
}
}
- Save and restart Cursor
Authentication
The Globalping MCP server supports two authentication methods:
- OAuth Authentication: Automatically handled by the server for secure access
- API Token Authentication: Manual token configuration via Authorization header
Both methods provide higher rate limits and priority access to the probe network.
Using Globalping API Token
The server automatically detects when an API token is provided in the Authorization header and uses it for authentication instead of OAuth.
Getting Your API Token
- Visit dash.globalping.io
- Sign in to your account
- Navigate to Tokens to generate a new API token
Configuration with Authentication
Streamable HTTP transport:
{
"mcpServers": {
"globalping": {
"url": "https://mcp.globalping.dev/mcp",
"headers": {
"Authorization": "Bearer YOUR_GLOBALPING_API_TOKEN"
}
}
}
}
Legacy SSE transport:
{
"mcpServers": {
"globalping": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.globalping.dev/sse",
"--header",
"Authorization: Bearer YOUR_GLOBALPING_API_TOKEN"
]
}
}
}
Connecting AI Assistants
You can use our MCP server with any MCP-compatible AI assistant, including:
- Claude Desktop
- Anthropic Assistants
- Cursor
- Windsurf
- Any custom implementation of the MCP protocol
See your tool's MCP documentation for details on connecting clients to this server.
Available Tools
ping- Perform a ping test to a targettraceroute- Perform a traceroute test to a targetdns- Perform a DNS lookup for a domainmtr- Perform an MTR (My Traceroute) test to a targethttp- Perform an HTTP request to a URLlocations- List all available Globalping probe locationslimits- Show your current rate limits for the Globalping APIgetMeasurement- Retrieve a previously run measurement by IDcompareLocations- Guide on how to run comparison measurementshelp- 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 definitionsrc/app.ts- OAuth web routessrc/api- Globalping API clientsrc/auth- Authentication utilitiessrc/config- Configuration and constantssrc/lib- Utility functionssrc/mcp- MCP tool handlerssrc/types- TypeScript type definitionssrc/ui- HTML templates
Add Globalping credentials
Add Globalping OAuth credentials:
npx wrangler secret put GLOBALPING_CLIENT_ID
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_namespacesin thewrangler.jsoncfile
FAQ
- What is the Globalping MCP server?
- Globalping is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for Globalping?
- This profile displays 73 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.7 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Extended AI Capabilities
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Context Enhancement
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Workflow Automation
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
- ›Basic understanding of MCP architecture and capabilities
- ›Access credentials for integrated services (if required)
- ›Willingness to experiment and iterate on configuration
Time Estimate
15-60 minutes depending on server complexity
Installation Steps
- 1.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 7.Document successful patterns for reuse
Troubleshooting
- ⚠MCP server not loading: Check config syntax, verify installation
- ⚠Connection errors: Check network, firewall, credentials
- ⚠Feature not working: Read server docs, check required parameters
- ⚠Performance issues: Monitor resource usage, check for network latency
- ⚠Conflicts with other servers: Check port assignments, namespace collisions
Best Practices▌
✓ Do
- +Read server documentation thoroughly before setup
- +Start with simple use cases to validate functionality
- +Test in non-production environment first
- +Monitor resource usage and performance
- +Keep servers updated for bug fixes and new features
- +Document configuration for team members
- +Use environment variables for sensitive configuration
✗ Don't
- −Don't grant overly permissive access to MCP servers
- −Don't skip reading security considerations in docs
- −Don't expose sensitive data without proper controls
- −Don't run untrusted MCP servers without code review
- −Don't ignore error messages—investigate root cause
💡 Pro Tips
- ★Combine multiple MCP servers for powerful workflows
- ★Create custom MCP servers for your specific needs
- ★Share successful configurations with team
- ★Use MCP inspector for debugging
- ★Join MCP community for tips and troubleshooting
Technical Details▌
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
- Model Context Protocol (MCP)
- JSON-RPC 2.0
- stdio or HTTP transport
Compatibility
- Claude Desktop
- Cursor IDE
- Custom MCP clients
When to Use This▌
✓ Use When
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid When
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
Integration▌
- →Tool composition: Chain multiple MCP tools in workflows
- →Context augmentation: Provide AI with relevant external data
- →Action delegation: Let AI execute tasks on external systems
- →Bidirectional sync: Keep AI context and external systems in sync
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
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Ratings
4.7★★★★★73 reviews- ★★★★★Isabella Smith· Dec 28, 2024
Globalping is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Ava Sethi· Dec 16, 2024
Useful MCP listing: Globalping is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Isabella Patel· Dec 16, 2024
Globalping is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Pratham Ware· Dec 12, 2024
I recommend Globalping for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Noah Brown· Dec 12, 2024
Globalping is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Meera Singh· Dec 12, 2024
Globalping reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Aanya Mehta· Dec 4, 2024
Strong directory entry: Globalping surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Tariq Bhatia· Nov 23, 2024
I recommend Globalping for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Isabella Ghosh· Nov 19, 2024
According to our notes, Globalping benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Ava Reddy· Nov 15, 2024
We evaluated Globalping against two servers with overlapping tools; this profile had the clearer scope statement.
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