# ShipSmart

> Use this tool when you need to validate shipping addresses or preview quotes from multiple carriers, such as UPS, FedEx, DHL, and USPS, through a unified API interface that accepts address and package details as input and returns validation results and quote estimates as output. It solves problems related to shipping logistics and carrier integration, streamlining the process for e-commerce and shipping services. Ideal for use cases requiring flexible and scalable shipping solutions, such as e-commerce platforms and logistics management systems.

Canonical page: https://skillsregistry.net/skills/nia194-shipsmart  
JSON: https://api.skillsregistry.net/v1/skills/nia194-shipsmart

## Description

A Python/FastAPI MCP server exposing shipping tools for address validation and quote previews. Uses a pluggable provider architecture supporting mock, UPS, FedEx, DHL, and USPS. Part of the ShipSmart platform ecosystem, centralizing tool definitions used by multiple services. Early-stage development with active feature roadmap.

## Trust

- **Trust score (0–1):** 0.57
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** maps-location
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/nia194-shipsmart)
- **Repository:** <https://github.com/nia194/shipsmart-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "nia194-shipsmart"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/nia194-shipsmart` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/nia194-shipsmart/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt