buffalo-ipsum 0.1.4

Filler text generator composed entirely of the word 'buffalo'. AI native.

buffalo-ipsum

Filler text generator composed entirely of the word "buffalo".

Buffalo buffalo Buffalo buffalo buffalo buffalo buffalo buffalo buffalo buffalo.
Buffalo buffalo buffalo buffalo buffalo. Buffalo buffalo Buffalo buffalo buffalo
buffalo buffalo buffalo buffalo buffalo buffalo buffalo.

Inspired by the linguistically valid English sentence that uses "buffalo" eight times. This package brings that energy to your placeholder text needs.

Install

pip install buffalo-ipsum

Usage

CLI:

buffalo-ipsum                        # 3 paragraphs (default)
buffalo-ipsum -t sentences -n 5      # 5 sentences
buffalo-ipsum -t words -n 10         # 10 words
buffalo-ipsum --famous               # the canonical 8-buffalo sentence
buffalo-ipsum -t art --cols 3        # ASCII art herd

Python API:

import buffaloipsum

buffaloipsum.word()                  # "buffalo"
buffaloipsum.words(5)                # ["buffalo", "buffalo", ...]
buffaloipsum.sentence()              # "Buffalo buffalo buffalo buffalo buffalo."
buffaloipsum.sentence(famous=True)   # "Buffalo buffalo Buffalo buffalo buffalo buffalo Buffalo buffalo."
buffaloipsum.paragraph()
buffaloipsum.text(3)
buffaloipsum.ascii_art(cols=2, rows=1)

--famous / famous=True emits the canonical 8-buffalo sentence — Buffalo buffalo Buffalo buffalo buffalo buffalo Buffalo buffalo. — verbatim. It's grammatically valid English; "Buffalo" serves as a proper noun (Buffalo, NY), a common noun (the animal), and a verb (to bully) all at once.

Default mode

Generates buffalo text locally with no dependencies and no network calls. All randomness is seeded from Python's random module; pass seed=N for reproducible output.

AI Native

Two integrations with the modern AI stack: a live mode that fetches each buffalo from a large language model, and an MCP server that exposes the generators as tools for autonomous agents.

Live mode

Routes every word through the Anthropic API. The output is always "buffalo", with each token validated end-to-end by a frontier model.

pip install 'buffalo-ipsum[live]'
export ANTHROPIC_API_KEY=sk-ant-...
buffalo-ipsum --live -t words -n 3

from buffaloipsum import live

live.word()     # -> "buffalo"  (one API call)
live.words(5)   # -> ["buffalo", ...] (five API calls)

Uses claude-haiku-4-5-20251001 by default. Override with --model on the CLI or model= in Python. Pass verbose=True (or -v on the CLI) to log requests, responses, and token usage to stderr.

MCP server

Exposes the buffalo-ipsum generators as Model Context Protocol tools so any MCP-compatible client — Claude Code, IDE assistants, custom agents — can invoke them.

pip install 'buffalo-ipsum[mcp]'

Wire it into Claude Code's settings.json:

{
  "mcpServers": {
    "buffalo-ipsum": {
      "command": "buffalo-ipsum-mcp"
    }
  }
}

Tools exposed:

Tool	Description
generate_words(count)	Space-separated buffalos.
generate_sentences(count, famous)	One sentence per line.
generate_paragraphs(count, famous)	Blank-line-separated paragraphs.
generate_ascii_art(cols, rows, gap)	Tiled ASCII-art herd.
famous_sentence()	The canonical 8-buffalo sentence.

The server speaks stdio. To launch it directly (e.g., for debugging):

buffalo-ipsum-mcp

License

MIT