mcpField
L
Lost & Found Label Generator

Lost & Found Label Generator

Local
github.com/aumshubDeveloper Tools0

About Lost & Found Label Generator

Generate free, beautiful lost and found labels with QR

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"LabelThemYours-MCP-Server": {
"command": "npx",
"args": [
"-y",
"mcp-remote"
]
}
}
}
Run commandnpx -y mcp-remote

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
npmmcp-remote

Tools

4

Saved tool list · updated 3w ago

ParameterTypeRequiredDescription
fullNamestringNoName on the label. Required. Ask one question at a time; max 18 characters.
phonestringNoPhone number. Required unless email is provided. Max 20 characters.
emailstringNoEmail address. Required unless phone is provided. Max 35 characters.
citystringNoCity on the label. Optional — user may say skip. Max 15 characters.
itemTypestringNoItem being labeled (e.g. Keys, Backpack). Required. Max 25 characters.
descriptionstringNoShort item description. Optional — user may say skip. Max 100 characters.
specialNotesstringNoNotes for the finder. Optional — user may say skip. Max 40 characters.
hasImportantDatabooleanNoMark as important item. Optional yes/no — user may say skip.
taglinestringNoPreset tagline or custom text. Required. Max 60 characters.
colorThemeenumNoLabel color theme. Required. One of: Red, Pink, OrangeRed, Purple, Green, SkyBlue, SlateBlue, Grey.Red | Pink | OrangeRed | Purple | Green | SkyBlue | SlateBlue | Grey
skippedFieldsarrayNoField names the user explicitly skipped (optional fields only, or phone when user prefers email only).

Details

The maintainer has not added details yet. Check the README in the repository.

Comments

Markdown supported

New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.