Projects sharing features with Awesome Claude Agents

PraisonAI is an autonomous AI agent platform that coordinates multiple LLM-powered agents for research, planning, and execution of complex workflows. It functions as a multi-agent orchestration framework, a workflow builder, and a Model Context Protocol server, while also providing retrieval-augmented generation through vector knowledge bases. Agents can interact via CLI, web, or standardized protocols with sandboxed code execution. The platform distinguishes itself with a rich set of agent communication protocols, including A2A, REST, WebSocket, voice and telephony integration, and MCP, allo

Mastra is an orchestration framework designed for building, deploying, and managing autonomous AI agents and multi-agent systems. It provides a comprehensive suite of primitives for creating resilient AI applications, including durable workflow orchestration, event-driven agent loops, and semantic memory management. By integrating these core components, the platform enables developers to build complex, multi-step processes that can reason about goals and execute tasks without manual intervention. The framework distinguishes itself through its focus on observability and secure, isolated execut

Hive is an artificial intelligence workflow automation engine and development platform designed for building and deploying autonomous agents. It provides a framework for orchestrating complex, multi-step business processes by coordinating tasks across multiple specialized agents using directed graph structures. The platform distinguishes itself through a focus on production-grade reliability and state management. It maintains persistent execution context and conversation history on disk, enabling crash recovery and continuity for long-running automated sessions. Furthermore, it incorporates a

auto-dev is an AI-native software engineering tool and multi-agent development platform designed to automate the entire software development lifecycle. It functions as an autonomous orchestrator that manages AI-driven coding, testing, and infrastructure configuration through declarative agent chains. The project is built on a Kotlin Multiplatform AI framework, allowing agent logic to run across diverse environments and device interfaces. The platform implements the Model Context Protocol to exchange tools and project information with external AI services. It distinguishes itself through the u

IntentKit is an open-source platform for deploying and managing a collaborative team of AI agents that can work together to complete complex tasks. It provides a self-hosted agent orchestrator that coordinates multiple agents through a modular pipeline of entrypoints, orchestration, and storage, all running as containerized services using Docker Compose or Swarm for production-grade deployment. The platform distinguishes itself by offering a plugin-based system for extending agent capabilities without modifying the core codebase, along with built-in integrations for connecting agents to socia

CrewAI is a multi-agent orchestration framework and autonomous agent workflow engine. It provides a system for coordinating autonomous AI agents with specific roles and goals to solve complex tasks through collaborative intelligence. The framework distinguishes itself through a collaborative AI agent system that enables multiple language model instances to share intelligence and execute multi-step objectives via role-playing. It incorporates human-in-the-loop mechanisms, allowing for manual review checkpoints to validate decisions and refine outcomes within autonomous execution paths. The pl

Kiro is an AI-powered development tool and multi-agent workflow orchestrator. It functions as a context-aware code generator and coding assistant that transforms natural language requirements into structured implementation plans and production-grade code. The system distinguishes itself through multi-agent task decomposition, where complex requirements are broken into sequenced tasks and assigned to specialized agents. It features multi-model orchestration to select specific language models based on reasoning complexity, cost, and latency, and includes a headless command-line interface for id

Goose is an autonomous coding assistant and extensible AI agent framework designed to automate software development workflows. It functions as an orchestration engine that can install, execute, and test code, as well as manage local files and shell commands. The platform is model-agnostic, providing a flexible interface to connect with diverse cloud-based or self-hosted large language model providers. It distinguishes itself through a standardized context protocol for integrating external tools and extensions, and a recipe system that allows users to define and repeat complex, multi-step AI w

Letta is a framework for building, deploying, and managing autonomous AI agents that maintain persistent state across long-term interactions. It provides a comprehensive suite of primitives for defining agents with configurable personas, modular memory blocks, and tool-use capabilities, enabling them to retain user preferences and conversation history over extended sessions. The platform distinguishes itself through its advanced memory management and orchestration capabilities. It allows agents to autonomously update their own memory, perform retrieval-augmented generation, and coordinate com

This project is an educational curriculum and architectural framework for building autonomous AI agents and multi-agent systems. It provides a structured learning path focused on the development of independent software components capable of planning, executing tasks, and utilizing external tools to achieve high-level goals. The framework emphasizes multi-agent system orchestration through distributed architectures where specialized agents collaborate using standardized communication protocols. It details specific design patterns such as dual-memory systems for maintaining short-term plans and

Langroid is a multi-agent orchestration framework and tool integration suite designed for building complex AI applications. It serves as a multi-modal integration layer that connects diverse local and remote language models with an agentic retrieval-augmented generation system. The project distinguishes itself through a collaborative message-exchange paradigm, allowing specialized agents to delegate tasks hierarchically and coordinate via structured communication. It features an advanced state management system for conversational AI, including the ability to rewind and prune conversation hist

Agency Swarm is a multi-agent orchestration framework and development kit designed to coordinate specialized AI agents through defined communication patterns and handoffs. It functions as a system for managing agent swarms, providing an API gateway to expose these coordinated collectives as production-ready HTTP endpoints. The project distinguishes itself through its Model Context Protocol integration layer, which connects agents to external data sources and capabilities. It implements specialized orchestration patterns, such as the orchestrator-worker model and role-based delegation, to tran

The BeeAI Framework is an LLM agent framework and multi-agent orchestration engine used to build autonomous agents that coordinate reasoning, tool execution, and complex workflows. It functions as a structured AI output controller and RAG integration library, providing a unified interface to manage multiple language model providers. The framework is distinguished by its implementation of the Model Context Protocol, allowing agents, tools, and models to be shared between different AI platforms and hosted as agentic tooling servers. It enables the design of collaborative agent teams through dec

cc-haha is a cross-platform desktop agent and computer use framework that enables large language models to control local operating systems through screenshots, clicks, and keystrokes. It functions as an AI coding workbench and orchestration platform, allowing for the management of multi-project workflows and the coordination of multiple agents executing complex tasks in parallel. The system includes a model backend gateway to connect various artificial intelligence providers and local models to autonomous agents. It features a centralized permission gate for authorizing sensitive commands and

Agent Squad is a multi-agent system orchestrator and language model agent orchestration framework. It serves as an AI workflow automation engine and tool integration layer designed to coordinate teams of specialized agents to solve complex tasks through routing, parallel execution, and state management. The project is distinguished by its ability to dynamically compose purpose-specific agents on-demand and route requests based on intent, language, or domain expertise. It supports advanced coordination patterns, including parallel subtask distribution, sequential task pipelines, and the abilit

Awesome Copilot is a comprehensive framework for autonomous software development, providing the infrastructure to orchestrate multi-agent teams and automate complex coding workflows. It functions as a centralized platform for managing AI-driven development, enabling developers to deploy specialized agents that interact with local files, terminal commands, and external APIs to execute end-to-end software delivery tasks. The project distinguishes itself through its focus on governance and extensibility, offering a suite of security controls, policy-based execution guardrails, and audit trails t

Agentscope is a comprehensive toolkit for developing and orchestrating autonomous multi-agent systems. It provides a unified framework for building agents that can reason, execute tools, and manage memory, enabling the creation of complex, collaborative workflows where multiple specialized agents interact to solve multi-step objectives. The platform distinguishes itself through a robust orchestration engine that supports both sequential and concurrent agent pipelines. It utilizes a centralized event bus for real-time telemetry, allowing developers to track agent reasoning, tool usage, and sys

This project is an autonomous agent workflow engine and multi-agent orchestration framework. It provides a runtime for managing agent lifecycles and a provider-agnostic abstraction layer for interacting with multiple large language model backends through standardized requests and structured outputs. The framework features a reliability layer for output verification, utilizing sampling-based majority voting and generator-evaluator feedback loops to refine model responses. It supports complex coordination patterns including sequential chaining, parallel execution with fan-in aggregation, and re

ECC is an LLM agent orchestration framework and cross-platform AI tooling suite designed to coordinate multi-model workflows. It provides a system for managing specialized agent roles, reusable skills, and structured planning to execute complex software development tasks across different AI-powered code editors. The project distinguishes itself as a Model Context Protocol manager, providing a configuration layer to integrate external servers and audit tool execution. It further implements an agentic security sandbox that restricts sensitive file access and scans for secret leakage to secure a

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,

Agent Squad is an LLM multi-agent orchestration framework designed to coordinate specialized agents to solve complex tasks. It functions as a system for managing agent teams and supervisors, utilizing a supervisor-led orchestration model to decompose large problems into manageable steps. The framework distinguishes itself through a combination of intent-based query routing and human-in-the-loop automation. It employs a hierarchical routing system to direct requests to the most appropriate agent or model, while integrating asynchronous messaging queues to route complex cases to human operators

Langflow is a low-code platform for designing and deploying multi-step AI agent pipelines and large language model sequences. It provides a visual environment to map logic and data flow between components, serving as an orchestrator for managing conversations and data retrieval across multiple autonomous agents. The platform distinguishes itself through a drag-and-drop interface that allows for the construction of complex AI pipelines without extensive boilerplate code. It enables the conversion of these internal workflows into standardized tools for external connectivity via the Model Contex

gptme is a multi-agent orchestration platform designed for autonomous software engineering, terminal-based AI integration, and RAG-enhanced code navigation. It enables the deployment of persistent agents and specialized subagents to decompose complex tasks and execute parallel technical workflows. The system distinguishes itself through a combination of vision-based GUI automation for controlling desktop applications and surgical patching mechanisms for targeted source code modifications. It utilizes git-based memory management to maintain a versioned history of agent identities, lessons, and

This project is a Java-based framework integration that provides an AI agent runtime, a graph-based AI workflow engine, and an LLM orchestration framework for Spring applications. It enables the development of stateful autonomous agents and the implementation of retrieval-augmented generation systems using document processing and vector databases. The framework distinguishes itself through a graph-based workflow runtime for designing complex AI pipelines with conditional routing and persistent state. It supports multi-agent orchestration via service-discovery coordination and provides human-i

Potpie is an LLM codebase analysis platform and multi-agent orchestration framework designed to act as an AI software engineer. It parses repositories into a structured code knowledge graph, enabling AI agents to perform multi-hop reasoning, dependency tracing, and grounded technical analysis across large codebases. The system distinguishes itself through a spec-driven development framework where agents generate detailed technical specifications and architecture plans before implementing multi-file code changes. It utilizes a durable execution engine to coordinate specialized AI personas for

Ralph is an autonomous software development platform that orchestrates artificial intelligence agents to implement complex features from start to finish. By converting high-level natural language descriptions into structured, machine-readable requirements, the system guides specialized agents through the entire software development lifecycle, including code generation, quality assurance, and repository management. The platform distinguishes itself through a multi-agent orchestration layer that delegates sub-tasks to specialized tools, ensuring that coding, testing, and refinement occur within

Antigravity-kit is a multi-agent orchestrator and routing engine designed to coordinate specialized large language model agents. It functions as a conversational workflow automation tool and a context management system that executes complex tasks through a chat interface. The system utilizes a routing engine to classify user requests and dispatch them to domain-expert agents. It employs a multi-agent orchestration model that allows specialist workers to operate in parallel and combine their outputs. To manage operational efficiency, the kit includes a memory layer for storing project convent