developer-tools

17TRACK Package Tracking

iamfiro

by iamfiro

Track USPS and US mail packages globally with 17TRACK's USPS tracking service—easy carrier ID and real-time delivery sta

Integrates with 17TRACK API to provide global package tracking across multiple carriers with fuzzy search for carrier identification and delivery status monitoring for e-commerce and customer service workflows.

github stars

3

0 commentsdiscussion

Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

Supports global carriersAutomatic carrier detectionRequires 17TRACK API token

best for

  • / E-commerce businesses tracking customer orders
  • / Customer service teams handling shipping inquiries
  • / Personal package tracking automation
  • / Logistics and fulfillment operations

capabilities

  • / Track packages from multiple carriers worldwide
  • / Auto-detect carrier from tracking number
  • / Monitor delivery status and location updates
  • / Specify carriers manually when needed
  • / Query package history and timeline

what it does

Tracks packages globally across multiple shipping carriers using the 17TRACK API. Automatically detects carriers from tracking numbers and monitors delivery status.

about

17TRACK Package Tracking is a community-built MCP server published by iamfiro that provides AI assistants with tools and capabilities via the Model Context Protocol. Track USPS and US mail packages globally with 17TRACK's USPS tracking service—easy carrier ID and real-time delivery sta It is categorized under developer tools.

how to install

You can install 17TRACK Package Tracking 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 runs locally on your machine via the stdio transport.

license

MIT

17TRACK Package Tracking is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

Parcel Tracking MCP Server

A Model Context Protocol (MCP) server for tracking parcel deliveries using the 17track.net API.

Features

  • Track parcel deliveries from various carriers
  • Automatic carrier detection
  • Support for manual carrier specification
  • Built with TypeScript and MCP SDK

Prerequisites

  • Node.js (v16 or higher)
  • npm or yarn
  • 17track.net API token

Installation

Install the package via npm:

npm install -g parcel-tracking-mcp-server

Or install locally:

npm install parcel-tracking-mcp-server

Configuration

Create a config.json file in your working directory with your 17track.net API token:

{
  "apiToken": "your-17track-api-token-here"
}

Note: The server looks for config.json in the current working directory where you run the command.

Getting a 17track.net API Token

  1. Visit 17track.net
  2. Sign up for an account
  3. Navigate to the API section
  4. Generate your API token
  5. Add it to your config.json file

Usage

Running the Server

If installed globally:

parcel-tracking-mcp-server

If installed locally:

npx parcel-tracking-mcp-server

Or if you're using it as a dependency in your project:

node node_modules/parcel-tracking-mcp-server/dist/index.js

MCP Client Configuration

To use this server with MCP clients (like Claude Desktop), add it to your MCP configuration:

{
  "mcpServers": {
    "parcel-tracking": {
      "command": "npx",
      "args": ["parcel-tracking-mcp-server"]
    }
  }
}

Or if installed globally:

{
  "mcpServers": {
    "parcel-tracking": {
      "command": "parcel-tracking-mcp-server"
    }
  }
}

Available Tools

tracking-delivery

Track a parcel delivery by providing a tracking number.

Parameters:

  • number (required): The tracking number of the parcel
  • carrier (optional): The carrier of the parcel (defaults to 'auto' for automatic detection)

Example:

// Track with automatic carrier detection
await trackingDelivery({
  number: "1234567890"
});

// Track with specific carrier
await trackingDelivery({
  number: "1234567890",
  carrier: "ups"
});

Supported Carriers

The server supports automatic carrier detection, but you can also specify carriers manually. Common carriers include:

  • UPS
  • FedEx
  • DHL
  • USPS
  • China Post
  • And many more (check 17track.net documentation for full list)

API Response Format

The server returns tracking information in JSON format, including:

  • Tracking status
  • Delivery progress
  • Timestamps
  • Location updates
  • Carrier information

Error Handling

The server includes comprehensive error handling:

  • API connection errors
  • Invalid tracking numbers
  • Missing configuration
  • Network timeouts

Development

Project Structure

├── index.ts          # Main server implementation
├── config.json       # Configuration file (create this)
├── package.json      # Dependencies and scripts
└── README.md         # This file

Dependencies

  • @modelcontextprotocol/sdk - MCP SDK for building servers
  • zod - Schema validation
  • node-fetch - HTTP requests (if needed for older Node.js versions)

License

MIT License

Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Submit a pull request

Support

For issues related to:

Changelog

v1.0.0

  • Initial release
  • Basic parcel tracking functionality
  • Support for automatic and manual carrier detection
  • Error handling and logging

FAQ

What is the 17TRACK Package Tracking MCP server?
17TRACK Package Tracking 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 17TRACK Package Tracking?
This profile displays 63 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. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 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

4.763 reviews
  • Henry Sharma· Dec 24, 2024

    I recommend 17TRACK Package Tracking for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Layla Choi· Dec 24, 2024

    I recommend 17TRACK Package Tracking for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Meera Chawla· Dec 8, 2024

    Strong directory entry: 17TRACK Package Tracking surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Yuki Khanna· Nov 27, 2024

    17TRACK Package Tracking is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Yuki Menon· Nov 19, 2024

    17TRACK Package Tracking reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Isabella Sharma· Nov 15, 2024

    We evaluated 17TRACK Package Tracking against two servers with overlapping tools; this profile had the clearer scope statement.

  • Nia Jackson· Nov 15, 2024

    Useful MCP listing: 17TRACK Package Tracking is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Aanya Park· Nov 15, 2024

    We evaluated 17TRACK Package Tracking against two servers with overlapping tools; this profile had the clearer scope statement.

  • Maya Menon· Oct 18, 2024

    We evaluated 17TRACK Package Tracking against two servers with overlapping tools; this profile had the clearer scope statement.

  • Yuki Verma· Oct 10, 2024

    Useful MCP listing: 17TRACK Package Tracking is the kind of server we cite when onboarding engineers to host + tool permissions.

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