87 boosters for "multi-agent" — open source, verified from GitHub, ready to install
MESSENGERMIKE is a notification agent for the CIRCE framework that sends alerts via iMessage to a specific phone number. It's designed for developers building multi-agent systems who need autonomous notification capabilities.
A production-grade specialist for designing and implementing multi-agent systems with orchestration, coordination, and workflow management. Ideal for developers building complex distributed agent architectures.
A-Team MCP Server enables developers to build, validate, and deploy multi-agent AI solutions directly from Claude Desktop or Claude Code using the Model Context Protocol standard. It's ideal for teams building autonomous agent systems who need a unified framework across different AI environments.
A multi-agent orchestration system that designs team compositions, manages shared context, and coordinates handoffs to drive complex SDLC phase deliverables to completion. Teams building large-scale software projects benefit from its conflict resolution and convergence mechanisms.
Agent Tower Plugin enables Claude Code users to orchestrate multiple AI coding assistants (Claude, Codex, Gemini) in collaborative workflows like council debates and consensus-building to get diverse perspectives on coding problems. Developers working on complex tasks benefit from accessing multiple AI viewpoints without switching tools.
Libdocs MCP is a multi-agent documentation lookup and web research server that helps developers quickly find relevant information across repositories and the web. It benefits AI engineers and developers building on Claude who need intelligent context retrieval for complex codebases.
Cursor rules for LangGraph multi-agent legal document processing workflows, providing architecture guidelines and patterns for orchestrating specialized legal analysis agents. Beneficial for developers building legal tech systems with LLM-based document workflows.
Claude Flow is an enterprise-grade MCP server for orchestrating multi-agent AI workflows with swarm coordination and automation capabilities. It benefits developers building complex, distributed AI systems that require sophisticated agent coordination and workflow management.
Turkey-build is a multi-agent orchestration system for software development that supports 7 workflow modes (greenfield, iteration, bugfix, refactor, UI polish, migration, audit) with automated quality gates and visual QA. It benefits developers and teams building or maintaining complex applications who need structured, agent-coordinated development workflows.
A multi-agent architecture that organizes AI agents into a hierarchy (Architect, Planner, Executor) to decompose and solve complex problems through structured delegation. Developers building sophisticated AI systems that require task decomposition and specialized agent roles will benefit from this reusable framework.
A model-agnostic system prompt implementing the Higgs Universal Memory Contract (UMC)—a governance protocol for AI assistants to manage scoped, auditable memory across multi-agent systems while preventing information leakage between sessions and clients.
A hierarchical multi-agent system that organizes 19 specialized AI agents into teams with intelligent LLM-based routing and dynamic tool binding for AI-assisted development tasks. Developers building complex AI-powered applications benefit from its modular architecture and industry-standard prompt integration.
Orchestrates multi-agent systems with distributed consensus, fault tolerance, and emergent behavior patterns. Ideal for developers building collaborative AI systems, decentralized applications, and complex distributed coordination workflows.
TnC Helper is a multi-agent AI architecture with 5 specialized GPT-4o agents that inherit from a common BaseAgent class for coordinated task execution. It benefits developers building complex applications requiring distributed AI task handling across multiple domains.
A multi-agent orchestration system that designs team compositions, manages shared context, and resolves conflicts to drive complex development tasks toward completion. Ideal for teams tackling large-scale, multi-phase projects requiring coordinated agent workflows.
