
Weixin Agent Sdk
If you need to connect an AI backend to WeChat without running a public server, this is the cleanest path I've seen. It uses long-polling through the Clawbot channel, so you just implement a simple Agent interface with a chat method and you're done. The OpenAI example in the source is actually complete and usable, not pseudocode. Handles multi-turn conversations, images, files, and auto-converts WeChat's SILK voice format to WAV. The ACP integration means you can bridge Claude Code or any compatible agent with a one-liner. One caveat: it stores credentials in ~/.openclaw/, so treat your dev machine accordingly. Works well for personal bots or internal tools where you control the WeChat account.
- skills.sh installs
- 1K
- GitHub stars
- 61
- last updated
- Jul 14, 2026
Install
$ npx -y skills add aradotso/trending-skills --skill weixin-agent-sdk --agent claude-codeInstalls into .claude/skills of the current project.
Files
weixin-agent-sdk
Skill by ara.so — Daily 2026 Skills collection.
weixin-agent-sdk is a TypeScript framework that bridges any AI backend to WeChat (微信) via the Clawbot channel. It uses long-polling to receive messages — no public server required — and exposes a minimal Agent interface so you can plug in OpenAI, Claude, or any custom logic in minutes.
Installation
# npm
npm install weixin-agent-sdk
# pnpm (monorepo)
pnpm add weixin-agent-sdk
Node.js >= 22 required.
Quick Start
1. Login (scan QR code once)
import { login } from "weixin-agent-sdk";
await login();
// Credentials are persisted to ~/.openclaw/ — run once, then use start()
2. Implement the Agent interface
import { login, start, type Agent } from "weixin-agent-sdk";
const echo: Agent = {
async chat(req) {
return { text: `You said: ${req.text}` };
},
};
await login();
await start(echo);
Core API
Agent Interface
interface Agent {
chat(request: ChatRequest): Promise<ChatResponse>;
}
Sponsors
Details
- Repository
- github.com/aradotso/trending-skills
- Category
- AI & Agent Building
- First seen
- May 16, 2026
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