# Square

> Use this tool when you need to integrate e-commerce capabilities, point-of-sale systems, or business analytics into AI applications using Square's payment and business management services. It provides a streamlined interface for Square API operations, supporting both sandbox and production environments, and handles secure API token management. Ideal for AI use cases requiring access to Square data, such as online transactions, inventory management, or sales reporting.

Canonical page: https://skillsregistry.net/skills/kvadratni-square  
JSON: https://api.skillsregistry.net/v1/skills/kvadratni-square

## Description

This MCP server implementation provides access to Square API functionality, enabling AI assistants to interact with Square's payment and business management services. Developed by Max Novich, it offers a streamlined interface for Square API operations, supporting both sandbox and production environments. The server is built using Python and leverages the squareup library for API interactions. It's particularly useful for AI applications requiring e-commerce capabilities, point-of-sale integrations, or business analytics based on Square data. The implementation focuses on secure API token management through environment variables and efficient request handling, making it suitable for various business-oriented AI use cases.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** finance
- **Updated:** 2026-04-25

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/kvadratni-square)
- **Repository:** <https://github.com/block/square-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": "kvadratni-square"
    }
  }
}
```

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

---
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