Cowsay▌

by mrseanchow
Create fun conversations with Cowsay, an ASCII art generator with 9 character variants for whimsical text formatting and
Generates ASCII art speech and thought bubbles using the cowsay library with 9 character variants including tux, dragon, elephant, and skeleton for adding whimsical text formatting to conversations.
best for
- / Adding humor to chat conversations
- / Creating fun terminal output in development
- / Generating ASCII art for documentation or presentations
capabilities
- / Generate ASCII art speech bubbles with custom messages
- / Create thought bubble ASCII art
- / Choose from 9 different characters including tux, dragon, elephant
- / List available character variants
what it does
Creates ASCII art speech and thought bubbles with customizable characters like cows, penguins, and dragons. Adds fun visual flair to text messages and conversations.
about
Cowsay is a community-built MCP server published by mrseanchow that provides AI assistants with tools and capabilities via the Model Context Protocol. Create fun conversations with Cowsay, an ASCII art generator with 9 character variants for whimsical text formatting and It is categorized under other. This server exposes 4 tools that AI clients can invoke during conversations and coding sessions.
how to install
You can install Cowsay in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
MIT
Cowsay is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
cowsay-mcp
<a href="https://github.com/mrseanchow/cowsay-mcp/stargazers"><img src="https://img.shields.io/github/stars/mrseanchow/cowsay-mcp" alt="Github Stars"></a> <a href="https://github.com/mrseanchow/cowsay-mcp/blob/main/LICENSE"><img src="https://img.shields.io/badge/license-MIT-purple" alt="License"></a> <a href="https://github.com/mrseanchow/cowsay-mcp/issues/new"><img src="https://img.shields.io/badge/Report a bug-Github-%231F80C0" alt="Report a bug"></a>
Cowsay MCP Server, providing ASCII art cow capabilities for LLMs. This implementation allows language models to generate fun ASCII art cows with custom messages.
🛠️ Tools
cowsay: Generate ASCII art with a cow saying your messagecowthink: Generate ASCII art with a cow thinking your messagelist_cows: List all available cow characters
📦 Installation
Installing via Smithery
To install cowsay-mcp for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @mrseanchow/cowsay-mcp --client claude
Manual Installation
npm install -g cowsay-mcp
Using npx
npx -y cowsay-mcp
🚀 Running on Cursor
Add this to your mcp.json file:
{
"mcpServers": {
"cowsay-mcp": {
"command": "npx",
"args": ["-y", "cowsay-mcp"]
}
}
}
🌊 Running on Windsurf
Add this to your ./codeium/windsurf/model_config.json file:
{
"mcpServers": {
"cowsay-mcp": {
"command": "npx",
"args": ["-y", "cowsay-mcp"]
}
}
}
🎨 Available Cow Characters
The server provides a wide variety of cow characters, including but not limited to:
default: The classic cowsmall: A smaller version of the default cowtux: A penguin charactermoose: A moose charactersheep: A sheep characterdragon: A dragon characterelephant: An elephant characterskeleton: A skeleton characterstimpy: A Stimpy character
And many more! Use the list_cows tool to see all available characters.
📝 Example Usage
cowsay Tool
{
"name": "cowsay",
"parameters": {
"message": "Hello from LLM!",
"cow": "tux"
}
}
cowthink Tool
{
"name": "cowthink",
"parameters": {
"message": "What should I say next?",
"cow": "moose"
}
}
list_cows Tool
{
"name": "list_cows",
"parameters": {}
}
📄 License
MIT License - see LICENSE file for details.
FAQ
- What is the Cowsay MCP server?
- Cowsay is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for Cowsay?
- This profile displays 32 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.7 out of 5—verify behavior in your own environment before production use.
Ratings
4.7★★★★★32 reviews- ★★★★★Noah Iyer· Dec 24, 2024
Strong directory entry: Cowsay surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★William Rahman· Dec 12, 2024
Cowsay is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Chaitanya Patil· Dec 8, 2024
Strong directory entry: Cowsay surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Piyush G· Nov 27, 2024
Cowsay is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Olivia Yang· Nov 15, 2024
Cowsay is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Noah Perez· Nov 3, 2024
According to our notes, Cowsay benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Olivia Lopez· Oct 22, 2024
Cowsay has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Shikha Mishra· Oct 18, 2024
We evaluated Cowsay against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Olivia Flores· Oct 6, 2024
We evaluated Cowsay against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Henry Brown· Sep 25, 2024
We wired Cowsay into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
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