Atmosphere is a Java-based framework for building and coordinating AI agents. It provides a real-time transport layer for streaming data via WebSockets, SSE, gRPC, and WebTransport, alongside a multi-agent orchestration framework for managing agent fleets through sequential, parallel, and graph-based execution workflows. The project features a durable workflow engine that persists agent state as snapshots, allowing long-running tasks to survive system restarts and incorporate human-in-the-loop approvals. It also implements Model Context Protocol servers to expose tools, resources, and prompt
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
This project is a framework for developing multimodal AI agents that function as programmable participants in real-time communication rooms. It enables the construction of agents that can see, hear, and speak by integrating speech-to-text, large language models, and text-to-speech pipelines to facilitate low-latency, natural conversations. The system is distinguished by its advanced orchestration of real-time media and conversational flow, including support for full-duplex speech, preemptive response generation, and sophisticated interruption management. It further differentiates itself throu
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
Claude Agent SDK is a Python library from Anthropic for building AI agents that use Claude’s tool‑calling, streaming, and session‑management capabilities. It provides a structured framework for intercepting and logging every tool call an agent makes, managing conversation sessions across multiple turns, and controlling which tools the agent is allowed to invoke through configurable permission rules.
Les fonctionnalités principales de anthropics/claude-agent-sdk-python sont : Claude Integration Frameworks, Typed JSON Schemas, Tool Access Controls, Agent Response Streamers, Agent Governance, Cross-Session Conversation Memories, In-Process MCP Server Implementations, Agent Response Streams.
Les alternatives open-source à anthropics/claude-agent-sdk-python incluent : atmosphere/atmosphere — Atmosphere is a Java-based framework for building and coordinating AI agents. It provides a real-time transport layer… mervinpraison/praisonai — PraisonAI is an autonomous AI agent platform that coordinates multiple LLM-powered agents for research, planning, and… livekit/agents — This project is a framework for developing multimodal AI agents that function as programmable participants in… letta-ai/letta — Letta is a framework for building, deploying, and managing autonomous AI agents that maintain persistent state across… disler/claude-code-hooks-mastery — This project is an extension framework and orchestration system for Claude Code that uses lifecycle hooks to intercept… strands-agents/sdk-python — This is an open-source Python SDK for building and orchestrating production-grade AI agents. It provides a unified…