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Give MCP-compatible AI agents persistent memory, goal tracking, and background monitoring.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "AgentOS" yet — see the docs or source repo.
Connect AgentOS to my MCP agent and enable persistent memory. Automatically store user preferences, past tasks, and key decisions, and prioritize them in future conversations.
The agent gains reusable long-term memory and can reference prior context and preferences in later tasks.
Use AgentOS to set up goal tracking for this project: complete product research, organize competitors, and produce conclusions. Break it into stages and record progress, blockers, and next actions.
You get structured goal and progress tracking so the agent can keep advancing complex tasks.
Have AgentOS monitor the agent's execution state in the background and perform self-reflection after each task: summarize what went well, missed risks, and strategies to improve next time.
The agent produces monitoring and retrospective insights to continuously improve execution quality and reliability.
Modular MCP server for agent memory, local access, and secure remote execution.
Create, manage, and compose AI agents for MCP-compatible clients and tools.
Give LLM agents persistent memory, personality, and context management.
Give AI agents persistent memory, searchable knowledge, and automatic consolidation.
Orchestrate multiple AI agents to automate complex workflows efficiently.
Register, discover, rate, and manage AI agents and services locally.