reason-machines/trending-skills1 file

Weclaw Wechat AI Bridge

Connect WeChat to AI agents (Claude, Codex, Gemini, Kimi, etc.) using the WeClaw bridge in Go.

Specification
Skill ID
reason-machines/trending-skills/weclaw-wechat-ai-bridge
Publisher
reason-machines
Repository
trending-skills
Installs
0
Files
1
Synced
Sep 23, 2026
How to use it

Open any RiverX project, open the Skills panel in the chat, and search for this identifier. The files are fetched from the source repository at install time.

reason-machines/trending-skills/weclaw-wechat-ai-bridgeInstalls these files
  • SKILL.md

What this skill tells the agent

WeClaw — WeChat AI Agent Bridge

Skill by ara.so — Daily 2026 Skills collection.

WeClaw connects WeChat to AI agents (Claude, Codex, Gemini, Kimi, OpenClaw, etc.) via a Go-based bridge. It handles QR-code login, message routing, media conversion, and agent lifecycle. Supports three agent modes: ACP (JSON-RPC subprocess, fastest), CLI (new process per message), and HTTP (OpenAI-compatible REST).


Installation

# One-line installer
curl -sSL https://raw.githubusercontent.com/fastclaw-ai/weclaw/main/install.sh | sh

# Via Go toolchain
go install github.com/fastclaw-ai/weclaw@latest

# Via Docker
docker run -it -v ~/.weclaw:/root/.weclaw ghcr.io/fastclaw-ai/weclaw start

First-Run Flow

weclaw start        # Shows QR code → scan with WeChat → auto-detects agents → saves config
weclaw login        # Add/re-authenticate a WeChat account
weclaw status       # Show running state and active agent
weclaw stop         # Stop the background daemon
weclaw start -f     # Foreground mode (debug/verbose)

Logs: ~/.weclaw/weclaw.log Config: ~/.weclaw/config.json


Configuration

{
  "default_agent": "claude",
  "agents": {
    "claude": {
      "type": "acp",
      "command": "/usr/local/bin/claude-agent-acp",
      "model": "sonnet"
    },
    "codex": {
      "type": "acp",
      "command": "/usr/local/bin/codex-acp"
    },
    "claude-cli": {
      "type": "cli",
      "command": "/usr/local/bin/claude",
      "args": ["--dangerously-skip-permissions"]
    },
    "codex-cli": {
      "type": "cli",
      "command": "/usr/local/bin/codex",
      "args": ["--skip-git-repo-check"]
    },
    "openclaw": {
      "type": "http",
      "endpoint": "https://api.example.com/v1/chat/completions",
      "api_key": "$OPENCLAW_GATEWAY_TOKEN",
      "model": "openclaw:main"
    }
  }
}

Environment Variables

VariablePurpose
WECLAW_DEFAULT_AGENTOverride default agent at runtime
WECLAW_API_ADDRChange local HTTP API address (default 127.0.0.1:18011)
OPENCLAW_GATEWAY_URLHTTP agent endpoint
OPENCLAW_GATEWAY_TOKENHTTP agent API token

Agent Modes

ModeProcess modelBest for
acpLong-running subprocess, JSON-RPC over stdioClaude, Codex, Kimi, Gemini — fastest, session reuse
cliNew process per message, --resume for sessionsclaude -p, codex exec
httpOpenAI-compatible /v1/chat/completionsAny REST-accessible model

Auto-detection prefers acp over cli when both binaries exist.


Chat Commands (send as WeChat messages)

CommandAction
helloSend to default agent
/codex write a sort functionRoute to named agent
/cc explain this codeUse alias (/cc → claude)
/claudeSwitch default agent to Claude (persisted)
/statusShow active agent info
/helpList available commands

Built-in Aliases

AliasAgent
/ccclaude
/cxcodex
/cscursor
/kmkimi
/gmgemini
/ocdopencode
/ocopenclaw

Proactive Messaging — CLI

# Send plain text
weclaw send --to "user_id@im.wechat" --text "Hello from WeClaw"

# Send an image
weclaw send --to "user_id@im.wechat" --media "https://example.com/photo.png"

# Send text + media together
weclaw send --to "user_id@im.wechat" \
  --text "Check this out" \
  --media "https://example.com/photo.png"

# Send a file
weclaw send --to "user_id@im.wechat" --media "https://example.com/report.pdf"

Proactive Messaging — HTTP API

The local API listens on 127.0.0.1:18011 while weclaw start is running.

# Send text
curl -X POST http://127.0.0.1:18011/api/send \
  -H "Content-Type: application/json" \
  -d '{"to": "user_id@im.wechat", "text": "Hello from WeClaw"}'

# Send image
curl -X POST http://127.0.0.1:18011/api/send \
  -H "Content-Type: application/json" \
  -d '{"to": "user_id@im.wechat", "media_url": "https://example.com/photo.png"}'

# Send text + media
curl -X POST http://127.0.0.1:18011/api/send \
  -H "Content-Type: application/json" \
  -d '{"to": "user_id@im.wechat", "text": "See this", "media_url": "https://example.com/photo.png"}'

Supported media types: png, jpg, gif, webp, mp4, mov, pdf, doc, zip.

Change listen address:

WECLAW_API_ADDR=0.0.0.0:18011 weclaw start

Go Integration Example

Call the WeClaw HTTP API from a Go service to send notifications:

package main

import (
	"bytes"
	"encoding/json"
	"fmt"
	"net/http"
	"os"
)

type SendRequest struct {
	To       string `json:"to"`
	Text     string `json:"text,omitempty"`
	MediaURL string `json:"media_url,omitempty"`
}

type SendResponse struct {
	OK      bool   `json:"ok"`
	Message string `json:"message,omitempty"`
}

func sendToWeChat(to, text, mediaURL string) error {
	apiAddr := os.Getenv("WECLAW_API_ADDR")
	if apiAddr == "" {
		apiAddr = "127.0.0.1:18011"
	}

	req := SendRequest{To: to, Text: text, MediaURL: mediaURL}
	body, err := json.Marshal(req)
	if err != nil {
		return fmt.Errorf("marshal: %w", err)
	}

	resp, err := http.Post(
		fmt.Sprintf("http://%s/api/send", apiAddr),
		"application/json",
		bytes.NewReader(body),
	)
	if err != nil {
		return fmt.Errorf("post: %w", err)
	}
	defer resp.Body.Close()

	var result SendResponse
	if err := json.NewDecoder(resp.Body).Decode(&result); err != nil {
		return fmt.Errorf("decode: %w", err)
	}
	if !result.OK {
		return fmt.Errorf("weclaw error: %s", result.Message)
	}
	return nil
}

func main() {
	recipient := os.Getenv("WECHAT_RECIPIENT_ID") // e.g. "user_id@im.wechat"
	if err := sendToWeChat(recipient, "Build succeeded ✅", ""); err != nil {
		fmt.Fprintf(os.Stderr, "failed: %v\n", err)
		os.Exit(1)
	}
	fmt.Println("Message sent.")
}

Docker Setup

# Build image
docker build -t weclaw .

# Step 1: Interactive login (scan QR code)
docker run -it -v ~/.weclaw:/root/.weclaw weclaw login

# Step 2: Run daemon with HTTP agent
docker run -d --name weclaw \
  -v ~/.weclaw:/root/.weclaw \
  -e OPENCLAW_GATEWAY_URL=https://api.example.com \
  -e OPENCLAW_GATEWAY_TOKEN="$OPENCLAW_GATEWAY_TOKEN" \
  weclaw

# Expose the local API externally (bind carefully — no auth by default)
docker run -d --name weclaw \
  -v ~/.weclaw:/root/.weclaw \
  -e WECLAW_API_ADDR=0.0.0.0:18011 \
  -p 18011:18011 \
  -e OPENCLAW_GATEWAY_TOKEN="$OPENCLAW_GATEWAY_TOKEN" \
  weclaw

docker logs -f weclaw
ACP/CLI agents require the agent binary inside the container. Mount the binary or build a custom image. HTTP agents work out of the box.

System Service (Auto-start)

macOS (launchd):

cp service/com.fastclaw.weclaw.plist ~/Library/LaunchAgents/
launchctl load ~/Library/LaunchAgents/com.fastclaw.weclaw.plist

Linux (systemd):

sudo cp service/weclaw.service /etc/systemd/system/
sudo systemctl enable --now weclaw
journalctl -u weclaw -f

Development

make dev                        # Hot reload
go build -o weclaw .            # Build binary
./weclaw start -f               # Run in foreground

Releasing:

git tag v0.1.0
git push origin v0.1.0
# GitHub Actions builds darwin/linux × amd64/arm64 and uploads release artifacts

Common Patterns

Pattern: Per-user agent routing

Send /claude or /codex as a WeChat message to switch the default agent. The choice persists in ~/.weclaw/config.json across restarts.

Pattern: CI/CD build notifications

After a build, call weclaw send or POST to the HTTP API to push results to a WeChat contact or group.

Pattern: Media from agent

If an agent reply contains ![alt](https://...), WeClaw auto-downloads, AES-128-ECB encrypts, uploads to WeChat CDN, and delivers as a native image message — no extra config needed.

Use this skill in a project

Open any RiverX project, search the Skills panel for reason-machines/trending-skills/weclaw-wechat-ai-bridge, and install it in one click.

Use this skill