ASKME-CLI
A command-line interface to prompt users for their next plan or confirmation.
[!NOTE] We'd love your help! If you try askme-cli on Windows or have compatibility fixes, PRs are very welcome👏.
ASKME-CLI
🤖 💬 ⚡ 🚀 ✨
An MCP (Model Context Protocol) server that provides user confirmation interface for AI assistants
Why
AI assistants often need user confirmation or next steps, but there's no simple way to get user input during MCP conversations.
This project provides a personal confirmation endpoint via terminal interface.
How to start
You will need to configure your MCP client to use ASKME-CLI.
Deploy the configuration using the instructions below.
Quick Setup with npx
# View help and configuration examples
npx askme-cli help
# Run directly (when called by MCP client)
npx askme-cli
Configure MCP Client
Add to your MCP client configuration file:
Cursor (.cursor/mcp_servers.json)
{
"mcpServers": {
"askme-cli": {
"command": "npx",
"args": ["askme-cli"],
"env": {
"ASKME_CLI_TERMINAL": "warp"
}
}
}
}
Other MCP Clients
{
"mcpServers": {
"askme-cli": {
"command": "npx",
"args": ["askme-cli"],
"env": {
"ASKME_CLI_TERMINAL": "iterm2"
}
}
}
}
Local Development
# Clone and install
git clone <your-repo-url>
cd askme-cli
npm install
# Build and run
npm run build
npm run start
How to use
Once configured, the AI assistant can use the ask_me tool to collect user confirmation:
- AI assistant calls
ask_metool with summary of completed work - ASKME-CLI opens a new terminal window with confirmation interface
- User enters next plan or confirmation and submits
- AI assistant receives user input to continue
Terminal Support
Configure via ASKME_CLI_TERMINAL environment variable:
| Terminal | Value | Description |
|---|---|---|
| Warp | warp | Default, modern terminal app |
| iTerm2 | iterm2 | Popular macOS terminal |
| Terminal | terminal | macOS system terminal |
| Kitty | kitty | Cross-platform terminal |
| Alacritty | alacritty | GPU-accelerated terminal |
| Hyper | hyper | Web-based terminal |
API Reference
ask_me Tool
Collects user's next plan or confirmation.
Parameters:
what_we_did(string): Summary of work completed by AI
Returns:
- User's input for next plan or confirmation
- Supports text and image input
Usage Examples
AI Assistant Integration
To use ASKME-CLI effectively in your AI assistant, add these rules to your system prompt:
- Must call the askme-cli.ask_me tool before ending any user prompt every time.
- All prompts starting with /tk, don't modify code or files, and call the askme-cli.ask_me tool before ending.
- When you have questions, always call the askme-cli.ask_me tool before ending.
- If you have ideas for new features or changes, explain them clearly, analyze their feasibility, and ask if I want to proceed.
Example Tool Call
{
"tool": "ask_me",
"parameters": {
"what_we_did": "I've completed setting up the database schema and created the user authentication endpoints. The API is now ready for testing."
}
}
Tech Stack
- TypeScript - Type-safe development
- React + Ink - Terminal UI framework
- MCP SDK - Model Context Protocol support
- Node.js - Runtime environment
License
MIT
関連サーバー
Alpha Vantage MCP Server
スポンサーAccess financial market data: realtime & historical stock, ETF, options, forex, crypto, commodities, fundamentals, technical indicators, & more
SpecBridge
Automatically generates MCP tools from OpenAPI specifications by scanning a folder for spec files. No configuration is needed and it supports authentication via environment variables.
Arcontextify
Convert ARC-56 smart contract specifications to MCP servers.
Snak
An agent engine for creating powerful and secure AI Agents powered by Starknet.
GroundDocs
A version-aware documentation assistant that connects LLMs to trusted, real-time docs to reduce hallucinations and provide accurate, version-specific responses.
MCP_Agent:RE
Fetches requirements and defect data from the TAPD platform to provide data support for AI clients.
Cntx UI
A minimal file bundling and tagging tool for AI development, featuring a web interface and MCP server mode for AI integration.
sqlew
ADR (Architecture Decision Record) for AI Agents – An MCP server that enables AI agents to create, query, and maintain architecture decision records in a structured SQL database
VectorMCP
A Ruby gem for building Model Context Protocol (MCP) servers to expose tools, resources, and prompts to LLM clients.
Everything
Reference / test server with prompts, resources, and tools
Enrichment MCP Server
Performs data enrichment on observables using third-party services via the security-cli Python package.