{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/7"}],"enrichment":{"capability":"AgentScope is a production-ready framework for building multi-agent systems with LLMs, providing abstractions for agent composition, tool management, model integration, and service deployment.","skillfed_tags":["multi-agent-framework","llm-orchestration","agent-service"],"use_cases":["Build a reasoning agent that breaks down tasks, calls tools (shell, file edit, search), and streams results to a frontend.","Deploy a multi-agent team service where specialized agents coordinate on complex tasks with leader-worker orchestration.","Connect agents to messaging platforms (Feishu, Discord) to answer questions and execute tasks from chat channels.","Implement RAG-augmented agents that retrieve and reason over documents in a multi-tenant service.","Compose agents with long-term memory (ReMe, Mem0) to maintain context across sessions.","Integrate with multiple LLM providers (OpenAI, Anthropic, DashScope, DeepSeek) without rewriting agent logic."],"what_it_does":"AgentScope is a framework for building and deploying multi-agent systems powered by large language models. It provides composable building blocks\u2014agents with reasoning-acting loops, tool management (Python tools, MCP servers, skills), model integration across major providers, context management with automatic compaction, and an event system for streaming reasoning and tool calls. The framework is designed to work with increasingly capable agentic LLMs, leveraging their reasoning and tool-use abilities rather than constraining them with rigid orchestration.\n\nBeyond the SDK layer, AgentScope includes a batteries-included agent service\u2014a FastAPI backend with a pre-built Web UI\u2014that turns agents into multi-tenant, multi-session applications. It supports agent teams with leader-worker orchestration, channels for connecting to messaging platforms (Feishu, Discord), RAG services, and a hub system for discovering and installing MCP servers and skills. The framework also provides isolated execution environments (local, Docker, K8s, E2B, Daytona) for safe tool and code execution.","worth_installing":"Yes. AgentScope is actively maintained, well-documented, and designed for production use. It offers a comprehensive toolkit for multi-agent systems with low install friction and permissive licensing. The 25 runtime dependencies are substantial but necessary for the breadth of features (LLM APIs, observability, async I/O, code parsing). Install if you are building agents that need tool use, multi-agent coordination, or service deployment; skip if you need only simple LLM chat."},"id":"agentscope","links":{"html":"https://skillfed.io/packages/agentscope","md":"https://skillfed.io/packages/agentscope.md","pypi":"https://pypi.org/project/agentscope/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-07","license_spdx":"Apache-2.0","license_treatment":"permissive","name":"agentscope","python_support":"supports_current","summary":"AgentScope: A Flexible yet Robust Multi-Agent Platform."},"popularity":{"monthly_downloads":251711,"position":8568,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"2.0.6"}