kaomoji
MCP Server that provides kaomoji between conversations for AI Agents
kaomoji-mcp
CLI-safe kaomoji for AI Agents at key interaction points
A Model Context Protocol (MCP) server that gives AI agents expressive kaomoji (ASCII emoticons) at key moments — thinking, celebrating, and apologizing. All kaomoji are CLI-safe: no full-width characters, no decorative Unicode, no rendering surprises in any terminal.
Searching for auth middleware
(..)
All tests passed! (^o^)/
Table of Contents
- Why kaomoji-mcp?
- Tools, Prompts & Resources
- Installation
- Quickstart
- Configuration by Client
- Development
- Running Tests
Why kaomoji-mcp?
Modern AI agents work through multiple sub-tasks before delivering an answer. Without visual indicators, the user sees nothing until the final response. kaomoji-mcp solves this by asking the agent to:
- Show a thinking kaomoji before each sub-task so the user can follow progress in real time
- Show a celebration kaomoji when a task completes successfully
- Show an apology kaomoji when results are not found or an error occurs
Because all characters are ASCII / half-width compatible, they render correctly in every terminal, IDE panel, and chat interface.
Tools, Prompts & Resources
Tools
| Tool | When to call | Key parameter |
|---|---|---|
thinking_kaomoji | Before each sub-task or reasoning phase | phase (string, max 80 chars); optional mcp_server |
celebrate_kaomoji | After a task completes successfully | intensity: "subtle" / "moderate" / "intense" |
apologize_kaomoji | On no-results, error, or user dissatisfaction | reason: "not_found" / "error" / "dissatisfied" |
thinking_kaomoji — Progress indicator. Call once per sub-task. Accepts an optional mcp_server parameter to show which external MCP server is being delegated to:
**Reading project files** [filesystem]
(._.)
celebrate_kaomoji — Completion signal. Choose intensity to match the moment:
subtle— gentle fix, formal context →(^-^)moderate— regular task done →(^o^)/intense— major breakthrough →\(^∀^)/
apologize_kaomoji — Failure signal. The reason field classifies the situation:
not_found— search returned no resultserror— unexpected error occurreddissatisfied— user expressed unhappiness
Prompt
| Prompt | Description |
|---|---|
react_with_kaomoji | Full behavior guide — load this prompt to give the agent detailed rules about when and how to use all three tools |
Resource
| URI | MIME | Description |
|---|---|---|
kaomoji://catalog | application/json | Full kaomoji database with all scenes, intensities, states, reasons, fallback strings, and bilingual tags |
Installation
Requirements
- Node.js ≥ 20
Option A — npx (no install, always latest)
No installation needed. Just reference the package in your MCP client config (see below) and the agent runtime will fetch it automatically.
npx kaomoji-mcp
Option B — Global install
npm install -g kaomoji-mcp
kaomoji-mcp # starts the stdio server
Option C — Local project clone
git clone https://github.com/frankunderwood-w/kaomoji_mcp_server.git
cd kaomoji-mcp
npm install
npm run build
node build/index.js # starts the stdio server
Option D — Local project by npm
mkdir my-project && cd my-project
npm init -y
npm install kaomoji-mcp
Quickstart
Once configured, your MCP-compatible agent will automatically receive the server instructions on connection and will know to call the tools at the right moments. You can also explicitly load the behavior guide by requesting the react_with_kaomoji prompt in your system prompt.
Configuration by Client
All configurations below launch the server over stdio transport. Replace node /absolute/path/to/build/index.js with npx kaomoji-mcp if you prefer to use the npm package directly.
Claude Desktop
Config file location:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"kaomoji": {
"command": "npx",
"args": ["-y", "kaomoji-mcp"]
}
}
}
Or, if you cloned the repo locally:
{
"mcpServers": {
"kaomoji": {
"command": "node",
"args": ["/absolute/path/to/kaomoji-mcp/build/index.js"]
}
}
}
Restart Claude Desktop after saving. The server should appear under Settings → Developer → MCP Servers.
Claude Code (CLI)
Add the server to your project or user configuration:
# Project-scoped (adds to .claude/mcp.json)
claude mcp add kaomoji -- npx -y kaomoji-mcp
# Or global
claude mcp add --global kaomoji -- npx -y kaomoji-mcp
Or edit .claude/mcp.json manually:
{
"mcpServers": {
"kaomoji": {
"command": "npx",
"args": ["-y", "kaomoji-mcp"]
}
}
}
Cursor
Config file location (global): ~/.cursor/mcp.json
Config file location (project): <project-root>/.cursor/mcp.json
{
"mcpServers": {
"kaomoji": {
"command": "npx",
"args": ["-y", "kaomoji-mcp"]
}
}
}
Or via the Cursor UI: Settings → Cursor Settings → MCP → click + Add new MCP server and enter the command above.
VS Code + GitHub Copilot
VS Code 1.99+ supports MCP servers natively when the GitHub Copilot extension is active.
Option 1 — Workspace config (.vscode/mcp.json):
{
"servers": {
"kaomoji": {
"type": "stdio",
"command": "npx",
"args": ["-y", "kaomoji-mcp"]
}
}
}
Option 2 — User settings (settings.json):
{
"mcp": {
"servers": {
"kaomoji": {
"type": "stdio",
"command": "npx",
"args": ["-y", "kaomoji-mcp"]
}
}
}
}
Open the Copilot Chat panel in Agent mode and the server will be available automatically.
Windsurf
Config file location: ~/.codeium/windsurf/mcp_config.json
{
"mcpServers": {
"kaomoji": {
"command": "npx",
"args": ["-y", "kaomoji-mcp"]
}
}
}
Or via the Windsurf UI: Windsurf Settings → Cascade → MCP Servers → click the + button.
Zed
Config file location: ~/.config/zed/settings.json
{
"context_servers": {
"kaomoji": {
"command": {
"path": "npx",
"args": ["-y", "kaomoji-mcp"]
}
}
}
}
Continue.dev
Config file location: ~/.continue/config.json (global) or .continue/config.json (project)
{
"mcpServers": [
{
"name": "kaomoji",
"command": "npx",
"args": ["-y", "kaomoji-mcp"]
}
]
}
Cline / Roo Cline
In VS Code, open the Cline extension sidebar → click the MCP Servers icon → Edit MCP Settings.
{
"mcpServers": {
"kaomoji": {
"command": "npx",
"args": ["-y", "kaomoji-mcp"],
"disabled": false,
"autoApprove": []
}
}
}
Smithery
This server is deployable on Smithery. The smithery.ts entry point exposes a configSchema (empty — no configuration required) and a createServer factory.
To deploy or install via Smithery CLI:
npx @smithery/cli install kaomoji-mcp
Development
# Clone and install
git clone https://github.com/frankunderwood-w/kaomoji_mcp_server.git
cd kaomoji-mcp
npm install
# Compile TypeScript → build/
npm run build
# Watch mode (recompiles on save)
npm run dev
# Type-check without emitting
npm run type:check
Project Structure
src/
├── index.ts # stdio entry point (CLI / npx)
├── smithery.ts # Smithery deployment entry point
├── create-server.ts # Server factory + SERVER_INSTRUCTIONS
├── tools/
│ ├── celebrate-kaomoji.ts
│ ├── thinking-kaomoji.ts
│ └── apologize-kaomoji.ts
├── prompts/
│ └── react-with.ts # react_with_kaomoji prompt
├── resources/
│ └── catalog.ts # kaomoji://catalog resource
└── data/
├── loader.ts # cached JSON loader
└── kaomoji.json # CLI-safe kaomoji database (75+ entries)
Running Tests
# Run all tests once
npm test
# Watch mode
npm run test:watch
The test suite covers:
| Suite | File | What it tests |
|---|---|---|
| Data loader | tests/data/loader.test.ts | JSON loading, schema shape, caching |
| CLI-safe validation | tests/data/cli-safe.test.ts | No full-width / decorative Unicode in database |
celebrate_kaomoji | tests/tools/celebrate.test.ts | Randomness, intensity, fallback, _instruction field |
thinking_kaomoji | tests/tools/thinking.test.ts | Phase names, mcp_server param, length limits |
apologize_kaomoji | tests/tools/apologize.test.ts | Reason codes, fallback, _instruction field |
| Integration | tests/integration/server.test.ts | Full server: tool list, prompt, resource, end-to-end calls |
All tests use in-memory MCP transport — no network or stdio required.
License
This project is licensed under the GNU General Public License v3.0.
Servidores relacionados
Bluesky
integrates with Bluesky API to query and search feeds and posts.
Voidly MCP Server
3 tools for global censorship intelligence (119 countries) + E2E encrypted agent-to-agent messaging with Double Ratchet and post-quantum crypto
AllVoiceLab
An AI voice toolkit with TTS, voice cloning, and video translation, now available as an MCP server for smarter agent integration.
Slack MCP Server
An MCP server for interacting with Slack workspaces using user tokens, without requiring bots or special permissions.
mcp-instagram-dm
Read, send, search, and manage Instagram DMs through AI assistants via MCP. 15 tools, cookie-based auth, single dependency.
Chatterbox TTS
Generates text-to-speech audio with automatic playback using the Chatterbox TTS model.
Slack
Interact with Slack workspaces to read and send messages directly through your AI assistant.
Gmail MCP
A standardized interface for managing, sending, and retrieving emails through the Gmail API.
Ntfy
An ntfy MCP server for sending/fetching ntfy notifications to your self-hosted ntfy server from AI Agents 📤 (supports secure token auth & more - use with npx or docker!)
Instantly
Manage email campaigns and leads using the Instantly.ai v2 API.