by nullpointexception-i · MCP Server · ★ 169
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
This project is an AI Agent orchestration platform. Driven by an LLM-based decision engine and combined with capabilities (built-in tools, MCP protocol, CLI execution, browser automation, etc.), it implements a primary closed loop of Perception → Planning → Execution → Feedback. It supports configuring different model providers: OpenAI, DeepSeek, QuickRouter (relay station), BigModel (Zhipu AI), LiteLLM. Screenshots ▶ Click to watch the video demo Quick Start for Development See: QUICKSTART.md Architecture 2.1 Overall Structure 2.2 Core Components 2.2.1 SessionRunner (ReAct Engine) Manages the complete execution lifecycle of an AI session, implementing the Plan → Act → Observe → Learn loop: Alignment with the ReAct pattern: , to achiev. It is categorized as a MCP Server with 169 GitHub stars.
agent-sphere is primarily written in Java. It covers topics such as agent, agentic-ai, java.
You can find installation instructions and usage details in the agent-sphere GitHub repository at github.com/nullpointexception-i/agent-sphere. The project has 169 stars and 3 forks, indicating an active community.
agent-sphere is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to agent-sphere on Agent Skills Hub include wren-engine, oreilly-ai-agents, octocode-mcp. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.