Repository History
5 repositories tagged with Agent Orchestration
SwarmClaw: Self-Hosted AI Agent Runtime for Autonomous Swarms
SwarmClaw is an open-source, self-hosted AI agent runtime and multi-agent framework designed for autonomous agent swarms. It offers durable agent memory, MCP tools, schedules, and delegation, supporting over 23 LLM providers including Claude, GPT, Gemini, OpenRouter, and Ollama. This platform serves as a practical alternative to solutions like Claude Code and LangChain for those seeking self-hosted AI agent orchestration.
Clowder AI: Orchestrating AI Teams for Collaborative Development
Clowder AI is an innovative platform designed to transform isolated AI agents into cohesive, collaborative teams. It emphasizes persistent identity, cross-model review, and shared memory, enabling AI models like Claude, GPT, and Gemini to work together seamlessly. This platform empowers users to orchestrate AI workflows, fostering a new paradigm for AI-driven development and co-creation.
awesome-cli-coding-agents: A Curated Directory of Terminal-Native AI Tools
The `awesome-cli-coding-agents` repository offers a comprehensive, curated directory of over 100 terminal-native AI coding agents. These powerful tools operate directly within your command line, enabling autonomous code reading, editing, and execution. The list also covers various harnesses and orchestration solutions for managing these agents.
LobeHub: Your Chief Agent Operator for AI Team Orchestration
LobeHub acts as a Chief Agent Operator, streamlining the management of your AI team. It enables hiring, scheduling, and reporting on agents for 24/7 operations, allowing users to maintain control without constant online presence. This platform transforms individual AI tools into a cohesive, productive team.
fast-agent: Build and Orchestrate Multimodal AI Agents and Workflows
fast-agent is a powerful Python framework designed for creating and interacting with sophisticated multimodal AI agents and workflows. It offers a simple, declarative syntax for defining agents, comprehensive model support, and unique features like end-to-end tested MCP (Multi-modal Communication Protocol) integration. Developers can rapidly build, test, and deploy complex agent applications with advanced capabilities such as structured outputs, vision, and various orchestration patterns.