# mcp-dunning-letters

> mcp-dunning-letters — theluckystrike-mcp-dunning-letters. Use this tool when you need to automate the process of sending reminders and notices for overdue invoice payments. It solves the problem of manually tracking and chasing late payments by providing a structured ladder of reminders and notices anchored to the due date. The tool takes input of overdue invoices and outputs a scheduled list of reminders, final notices, and aging reports, integrating with platforms like Claude Desktop, Claude Code, and Cursor.

Canonical page: https://skillsregistry.net/skills/theluckystrike-mcp-dunning-letters  
JSON: https://api.skillsregistry.net/v1/skills/theluckystrike-mcp-dunning-letters

## Description

Model Context Protocol (MCP) server for dunning letters and overdue invoice payment reminders: reminder, final notice and aging. Chase overdue invoices on a ladder anchored to the due date: reminder 1, reminder 2, the final notice, with the aging and the day's chase list. Works with Claude Desktop, Claude Code and Cursor.

## Trust

- **Trust score (0–1):** 0.95
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/theluckystrike/mcp-dunning-letters)

## 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": "theluckystrike-mcp-dunning-letters"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/theluckystrike-mcp-dunning-letters` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/theluckystrike-mcp-dunning-letters/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