Alris

Alris – Natural‑Language Driven Automation

Alris is a Model Context Protocol (MCP) server that turns plain English instructions into automated actions across web and local applications. By exposing a set of high‑level commands such as , , , and , it lets AI assistants like Claude orchestrate real‑world tasks without needing to write scripts or trigger APIs manually. This solves the common pain point of bridging conversational AI with operational systems, enabling developers to build productivity workflows that feel like talking to a human coworker.

The server’s core value lies in its seamless integration between natural‑language processing, web automation, and real‑time monitoring. A FastAPI backend hosts an automation engine powered by Playwright for browser control and LangChain for language understanding. When a client sends an MCP request, the engine parses the intent, resolves any necessary parameters, and executes the corresponding action—whether that’s querying a search engine, navigating to a URL, or streaming media. The result is returned instantly through WebSocket communication, allowing the AI assistant to provide immediate feedback or follow‑up queries. This tight loop turns a conversation into a live, interactive session with external tools.

Key capabilities include:

• Intuitive command set that maps directly to everyday tasks, reducing the learning curve for developers.
• Real‑time execution monitoring so AI assistants can report status, handle errors, and adjust plans on the fly.
• WebSocket‑based communication for low‑latency, bidirectional interaction essential in conversational contexts.
• Cross‑platform architecture with a React/Next.js front end and Python FastAPI back end, making it easy to deploy on Linux, macOS, or Windows.
• Security features such as CORS protection, input validation, authentication, and rate limiting that safeguard automated actions.

Typical use cases span personal productivity tools (e.g., “search the latest news about AI”), developer pipelines (e.g., “open GitHub PR #123”), media consumption (“play music of The Beatles”), and even complex workflows that combine multiple commands into a single orchestrated task. By exposing these actions through MCP, Alris allows AI assistants to act as a unified control plane for diverse applications, streamlining repetitive work and freeing developers to focus on higher‑level logic.