ms-agent is an LLM agent framework and multi-agent orchestration system designed to build autonomous entities that combine large language models with tool calling and structured workflows. It serves as a tool integration platform and workflow engine for executing complex tasks through the coordination of specialized agents.
The project distinguishes itself through a multimodal agent workflow engine capable of automating the production of text, images, and video. It features a sandboxed code execution environment for running generated code and quantitative data analysis in isolated containers, alongside a self-healing execution model that uses language models to analyze runtime failures and automatically generate fixes.
The system covers broad capability areas including deep research automation, automated software generation, and financial research analysis. It implements these through a dependency-aware directed acyclic graph for task scheduling, hybrid-search skill matching, and state-aware memory management to maintain context across extended interactions.
An interactive web interface is provided for real-time chatting and monitoring agent execution via bidirectional connections.