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Astonish is a local AI agent platform inspired by OpenClaw, implemented in Go as a single binary file. It supports dynamic tool calling, automatic workflow refinement, a semantic memory system, and the MCP protocol, allowing users to create complex AI workflows via YAML configuration without writing extensive code.
Section 01
Astonish is a local AI agent platform inspired by OpenClaw, implemented in Go as a single binary file. It supports dynamic tool calling, automatic workflow refinement, a semantic memory system, and the MCP protocol, allowing users to create complex AI workflows via YAML configuration without writing extensive code.
Section 02
In the field of AI agents, most solutions are either too complex requiring extensive programming or too simplistic to meet practical needs. Astonish aims to strike a balance between the two, providing a powerful yet easy-to-use local AI agent platform.
This project is deeply inspired by OpenClaw— which pioneered several innovations in the personal AI assistant space, including resident daemons, skills as Markdown, multi-channel messaging, and a tool-first architecture. Astonish reimplements these concepts in Go and adds a unique feature: automatic workflow refinement.
The core principles can be summarized as:
Section 03
Astonish adopts a modular architecture, with core components including:
Section 04
The agent dynamically solves problems through LLM-driven tool-use loops. It decides which tools to call and how to combine toolchains based on task requirements, enabling multi-step tasks without predefined workflows.
It has 58 built-in tools covering:
Section 05
Astonish natively supports the Model Context Protocol (MCP), allowing any MCP server to be plug-and-play. This means users can easily add external capabilities like GitHub, Slack, and databases, extending agent functionality without modifying code.
Section 06
Supports over 15 AI providers, including:
Users can dynamically switch providers and models during a session; the system supports hot-swapping without restarting.
Section 07
Astonish's most distinctive feature is its three-step workflow refinement mechanism:
Section 08
The agent dynamically handles user requests, calling necessary tools to complete multi-step tasks. The entire execution process is fully recorded as an execution trace.
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