🤖 YETR AI Agent - Your Enhanced Task Runner

What is YETR AI Agent?

YETR AI Agent is an advanced AI agent system that connects to multiple MCP (Model Context Protocol) servers simultaneously for intelligent task automation. It is designed for developers and teams needing multi-server orchestration, with a React/Next.js frontend, FastAPI backend, PostgreSQL database, and Redis cache.

How to use YETR AI Agent?

You can try the live interactive demo at yethikrishna.github.io/yetr-ai-agent. For local development, clone the repository, then run npm install && npm run dev in the frontend directory, pip install -r requirements.txt && uvicorn app.main:app --reload in the backend directory, or use docker-compose up -d for the Docker setup. Configure MCP server connections and environment variables (e.g., DATABASE_URL, OPENAI_API_KEY) as described in the README.

Key features of YETR AI Agent

• Sophisticated natural language processing and task decomposition
• Connects to 50+ MCP servers simultaneously
• Real-time streaming chat with context memory
• Automatic tool discovery and intelligent routing
• Parallel execution with dependency management
• JWT authentication and role-based access control

Use cases of YETR AI Agent

• Repository analysis, code quality assessment, and multi-platform deployment automation
• Task orchestration across tools with progress tracking and reporting
• Multi-source data aggregation and real-time synchronization between systems
• CI/CD pipeline optimization and code review documentation generation

FAQ from YETR AI Agent

What MCP servers can YETR AI Agent connect to?

It connects to 50+ MCP servers including GitHub, GitLab, File Systems, Databases, Email, Calendar, Slack, Discord, Web Search, APIs, RSS feeds, OpenAI, Anthropic, and local AI models.

What are the runtime requirements?

Backend requires Python 3.11+, PostgreSQL, Redis, and a FastAPI server. Frontend requires Node.js with React 18, Next.js 14, TypeScript, and Tailwind CSS. A Docker setup is recommended for production-like environments.

Is there a live demo available?

Yes, an interactive chat demo is available at yethikrishna.github.io/yetr-ai-agent, where you can ask about GitHub analysis, deployment guidance, MCP integration, architecture, and features with real-time responses.

How is data secured?

Authentication uses JWT with refresh tokens, authorization is role-based (RBAC), all communications are encrypted with TLS 1.3, and the system includes comprehensive input validation and rate limiting.

What performance can I expect?

Response time is under 100 ms for simple queries, throughput supports 1,000+ concurrent conversations, and the architecture allows horizontal scaling with load balancing for 99.9% availability.