MCP server

Tiny Utils

net.bigfloppy.utils/utils

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

AI-writing-tells detector (rules-based) + CSV/JSON, hashing, slugs, word counts, UUIDs. Free.

Website Source

At a glance

Type

MCP server

Publisher

bigfloppy.net (verified by the MCP Registry)

Status

Working at last check

Tools

9

Token cost

About 564 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http utils https://utils.bigfloppy.net/mcp

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.utils]
url = "https://utils.bigfloppy.net/mcp"

Gemini CLI

{"mcpServers":{"utils":{"httpUrl":"https://utils.bigfloppy.net/mcp"}}}

Cursor

{"mcpServers":{"utils":{"url":"https://utils.bigfloppy.net/mcp"}}}

VS Code

{"servers":{"utils":{"type":"http","url":"https://utils.bigfloppy.net/mcp"}}}

Antigravity

agy mcp add utils https://utils.bigfloppy.net/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"utils","server_url":"https://utils.bigfloppy.net/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"utils","server_url":"https://utils.bigfloppy.net/mcp"}

Tools

• aitells ~81 tokens
  AI-writing-tells score 0-99 with verdict, word/sentence counts. Rules-based, deterministic, no LLM. Input: text to check.
• aitells_report ~98 tokens
  Full AI-writing-tells report: score, every matched tell with example sentences, style stats (em-dash rate, rule-of-three, sentence-length uniformity). Deterministic, no LLM.
• csv2json ~63 tokens
  Convert CSV text to a JSON array of objects (first row = headers).
• hash ~72 tokens
  Hash text with md5, sha1, sha256 or sha512 (default sha256).
• json2csv ~66 tokens
  Convert a JSON array of objects to CSV text.
• slug ~44 tokens
  Turn text into a URL slug.
• time ~36 tokens
  Current unix + ISO UTC time.
• uuid ~54 tokens
  Generate random UUIDv4s (1-100, default 5).
• wordcount ~50 tokens
  Count words, characters and lines of text.

Browse

• Spreadsheets
• Calling other AI models

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