What is AssistStudio Runner?

AssistStudio Runner is a headless automation engine designed to schedule and execute natural language LLM tasks on Windows, delivering results through various communication channels.

How does AssistStudio Runner schedule tasks?

It integrates seamlessly with Windows Task Scheduler, automatically converting cron expressions into native 'schtasks' entries for reliable, automated execution of your LLM workflows.

How are task results delivered?

AssistStudio Runner delivers task outcomes through configured Outbox channels such as Slack, Telegram, and Email, ensuring results reach you where you need them.

Is credential management secure?

Yes, API keys and sensitive credentials are securely stored and managed using Windows Credential Manager (DPAPI), ensuring your data is protected and private.

AssistStudio Runner

Name: AssistStudio Runner
Author: fieldcure

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Automates natural language LLM tasks, scheduling execution and delivering results through various communication channels.

AssistStudio Runner functions as a headless LLM task automation engine, designed to schedule and execute natural language tasks with precision. Operating as a Model Context Protocol (MCP) server, it seamlessly integrates with various LLM providers like Claude, OpenAI, Gemini, Ollama, and Groq. It leverages Windows Task Scheduler for robust scheduling based on cron expressions and securely manages API keys. Once tasks are complete, it delivers results through diverse channels such as Slack, Telegram, and Email, making it an ideal solution for automating routine AI-driven workflows.

主要功能

01Seamless integration with Windows Task Scheduler for cron-based task scheduling

02Support for multiple LLM providers including Claude, OpenAI, Gemini, Ollama, and Groq

03Delivers task results via Outbox channels such as Slack, Telegram, and Email

04Secure credential management using Windows Credential Manager (DPAPI)

050 GitHub stars

06Dual-mode operation for task management (MCP server) and headless execution (CLI)

使用案例

01Automate daily or weekly LLM-driven reports, like summarizing competitor news and sending to Slack.

02Schedule natural language tasks to process information and deliver results via messaging platforms.

03Orchestrate recurring AI agent workflows across multiple LLM providers for various automation needs.