π€ YETR AI Agent - Your Enhanced Task Runner
LocalAbout π€ YETR AI Agent - Your Enhanced Task Runner
YETR AI Agent is a web-based MCP task runner for automating complex, multi-step tasks. It combines task planning, tool use, and context management in an interface for running and monitoring agent workflows.
Key features
- 01Multi-step task orchestration
- 02Task planning
- 03Code, web, file, and API tools
- 04Conversation and task context
- 05Extensible tools and skills
Use cases
- 01Automating multi-step tasks
- 02Searching the web and reading files
- 03Chaining AI calls across a workflow
MCP support
It is an MCP-based agent designed for standardized tool use. The README describes the agent but does not specify which MCP servers it connects to.
Configuration
Local server config is the same for every client. Copy it into your clientβs MCP config file.
We havenβt collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project README
Yetr AI Agent
Enhanced MCP Task Runner Agent
Yetr AI Agent is an enhanced Model Context Protocol (MCP) task runner agent built with Next.js 14, React, and Tailwind CSS, designed for intelligent task automation, tool use, and AI agent workflows.
Overview
yetr-ai-agent is a powerful AI agent built on the Model Context Protocol (MCP), designed as an enhanced task runner for complex AI workflows. Built with Next.js 14 App Router, React 18, and Tailwind CSS, it provides a modern web interface for running, managing, and monitoring AI agent tasks with multi-platform deployment support.
Features
- MCP-Compliant Agent - Built on the Model Context Protocol for standardized AI tool use
- Enhanced Task Runner - Execute complex, multi-step AI tasks with intelligent orchestration
- Next.js 14 App Router - Modern React Server Components architecture
- Multi-Platform Deployment - Vercel, Netlify, GitHub Pages, and Docker support
- SEO Optimized - Built-in sitemap.xml, robots.txt, and custom domain support
- Beautiful UI - Tailwind CSS with Heroicons for a clean, responsive interface
- Type-Safe - Full TypeScript coverage
- Custom Domain Ready - CNAME file included for custom domain configuration
- Docker Support - docker-compose.yml for containerized deployment
Tech Stack
| Layer | Technology |
|---|---|
| Framework | Next.js 14 (App Router) |
| UI | React 18 |
| Styling | Tailwind CSS 3 |
| Icons | Heroicons React |
| Language | TypeScript |
| Utilities | clsx for className composition |
| Deployment | Vercel / Netlify / GitHub Pages / Docker |
Quick Start
# Clone the repository
git clone https://github.com/yethikrishna/yetr-ai-agent.git
cd yetr-ai-agent
# Install dependencies
npm install
# Set up environment
cp .env.example .env.local
# Configure your AI model API keys and MCP settings
# Start development server
npm run dev
# Build for production
npm run build
# Start production server
npm start
Deployment
Vercel (Recommended)
# One-click deployment via Vercel CLI or connect your repo
vercel deploy
Netlify
See netlify.toml for build configuration. The project includes .netlifyignore for optimized builds.
GitHub Pages
See GITHUB_PAGES_SETUP.md for instructions. The project includes _config.yml for Jekyll compatibility.
Docker
docker-compose up -d
Project Structure
yetr-ai-agent/
βββ src/ # Next.js source (App Router)
βββ frontend/ # Frontend-specific assets
βββ public/ # Static assets (robots.txt, sitemap.xml)
βββ package.json
βββ next.config.js # Next.js configuration
βββ tailwind.config.js
βββ tsconfig.json
βββ postcss.config.js
βββ next-env.d.ts
βββ docker-compose.yml
βββ netlify.toml
βββ vercel.json
βββ CNAME # Custom domain config
βββ sitemap.xml
βββ robots.txt
βββ DEPLOYMENT.md
βββ GITHUB_PAGES_SETUP.md
Agent Capabilities
- Tool Use - Execute code, search the web, read files, and interact with APIs
- Task Planning - Break down complex goals into executable steps
- Context Management - Maintain conversation and task context across interactions
- Multi-Step Reasoning - Chain together multiple AI calls for complex workflows
- Extensible - Easy to add new tools, skills, and capabilities
Contributing
Contributions to enhance the agent's capabilities are welcome! Please feel free to submit issues or pull requests.
License
This project is licensed under the terms specified in the repository.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.