Run a lightweight personal AI agent with Nanobot
Use Nanobot to configure a lightweight local personal agent with model providers, MCP tools, memory, chat channels, search, and gateway deployment paths.
npx skills add agentskillexchange/skills --skill run-a-lightweight-personal-ai-agent-with-nanobot
Use Nanobot when an operator wants a small personal-agent runtime that can be installed locally, connected to model providers and MCP tools, and run through terminal, WebUI, chat channels, or gateway-style deployment. The workflow is to install the nanobot-ai package, run onboarding, configure provider credentials and tool permissions, then start the agent loop or gateway for the target workspace.
What this skill actually does
Invoke this instead of building a custom personal-agent shell when the goal is to stand up a readable, hackable agent with memory, MCP integration, search, chat surfaces, and long-running objectives. The scope boundary is operating Nanobot as its own lightweight agent runtime; it is not a general OpenClaw plugin, model provider, or hosted assistant product.
Inputs are Python 3.11+, provider API keys or local model endpoints, MCP server definitions, optional search/chat credentials, and a target workspace. Outputs are a configured Nanobot agent, local runtime state, tool/plugin connections, and an operational path for terminal, WebUI, channel, or gateway use.