
Weclaw Wechat Ai Bridge
- 923 installs
- 66 repo stars
- Updated July 9, 2026
- aradotso/trending-skills
weclaw-wechat-ai-bridge is an agent skill that connects WeChat to AI agents through the Go-based WeClaw bridge for developers who need WeChat as a messaging interface for Claude, Codex, Gemini, or Kimi backends.
About
weclaw-wechat-ai-bridge is a Go integration skill that connects WeChat to AI agents including Claude, Codex, Gemini, Kimi, and OpenClaw through the WeClaw bridge. The skill covers WeClaw setup and configuration, QR-code WeChat login, inbound and outbound message routing, media conversion, and bridging WeChat traffic to OpenAI-compatible APIs. Triggers include proactive messaging, WeChat bot backends, and agent integrations where users message from WeChat instead of a web UI. WeClaw handles protocol details so agent runtimes focus on inference and tool use. Developers reach for weclaw-wechat-ai-bridge when shipping agent products to WeChat users in markets where WeChat is the primary messaging surface and a dedicated bridge is required beyond standard HTTP webhooks.
- Connects WeChat to Claude, Codex, Gemini, Kimi and other agents
- Three agent modes: ACP (JSON-RPC subprocess), CLI, and HTTP (OpenAI-compatible REST)
- Handles QR-code login, message routing, media conversion and agent lifecycle
- Supports proactive messaging and WeChat bot with AI backend
- One-line installer, Go binary, or Docker deployment
Weclaw Wechat Ai Bridge by the numbers
- 923 all-time installs (skills.sh)
- +7 installs in the week ending Jul 28, 2026 (Skillselion tracking)
- Ranked #1,138 of 16,659 AI & Agent Building skills by installs in the Skillselion catalog
- Security screen: CRITICAL risk (skills.sh audit)
- Data as of Jul 28, 2026 (Skillselion catalog sync)
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| Installs | 923 |
|---|---|
| repo stars | ★ 66 |
| Security audit | 0 / 3 scanners passed |
| Last updated | July 9, 2026 |
| Repository | aradotso/trending-skills ↗ |
How do you connect WeChat to an AI agent backend?
Connect WeChat as a messaging interface for their AI agents.
Who is it for?
Developers building WeChat-facing AI bots who need Go-based WeClaw setup with Claude, Codex, Gemini, Kimi, or OpenAI-compatible agent backends.
Skip if: Developers targeting Slack, Discord, or SMS only, or teams without WeChat access who do not need a China-market messaging bridge.
When should I use this skill?
A developer asks to connect WeChat to Claude, configure WeClaw, bridge WeChat with an OpenAI-compatible API, or enable proactive WeChat agent messaging.
What you get
Configured WeClaw Go bridge with WeChat QR login, message routing rules, media handling, and agent API integration for bidirectional chat.
- WeClaw configuration
- Message routing setup
- Agent API bridge wiring
Files
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
| Variable | Purpose |
|---|---|
WECLAW_DEFAULT_AGENT | Override default agent at runtime |
WECLAW_API_ADDR | Change local HTTP API address (default 127.0.0.1:18011) |
OPENCLAW_GATEWAY_URL | HTTP agent endpoint |
OPENCLAW_GATEWAY_TOKEN | HTTP agent API token |
---
Agent Modes
| Mode | Process model | Best for |
|---|---|---|
acp | Long-running subprocess, JSON-RPC over stdio | Claude, Codex, Kimi, Gemini — fastest, session reuse |
cli | New process per message, --resume for sessions | claude -p, codex exec |
http | OpenAI-compatible /v1/chat/completions | Any REST-accessible model |
Auto-detection prefers acp over cli when both binaries exist.
---
Chat Commands (send as WeChat messages)
| Command | Action |
|---|---|
hello | Send to default agent |
/codex write a sort function | Route to named agent |
/cc explain this code | Use alias (/cc → claude) |
/claude | Switch default agent to Claude (persisted) |
/status | Show active agent info |
/help | List available commands |
Built-in Aliases
| Alias | Agent |
|---|---|
/cc | claude |
/cx | codex |
/cs | cursor |
/km | kimi |
/gm | gemini |
/ocd | opencode |
/oc | openclaw |
---
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 weclawACP/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.plistLinux (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 foregroundReleasing:
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 , WeClaw auto-downloads, AES-128-ECB encrypts, uploads to WeChat CDN, and delivers as a native image message — no extra config needed.
Pattern: Disable permission prompts for headless use
{
"claude": { "type": "cli", "command": "/usr/local/bin/claude",
"args": ["--dangerously-skip-permissions"] },
"codex": { "type": "cli", "command": "/usr/local/bin/codex",
"args": ["--skip-git-repo-check"] }
}ACP agents handle permissions automatically and do not need these flags.
---
Troubleshooting
| Symptom | Fix |
|---|---|
| QR code not appearing | Run weclaw login explicitly; ensure terminal supports UTF-8 |
| Agent not auto-detected | Check binary is on $PATH; run weclaw status |
connection refused on HTTP API | Confirm weclaw start is running; check WECLAW_API_ADDR |
| Agent permission prompts block responses | Add --dangerously-skip-permissions (Claude) or --skip-git-repo-check (Codex) to args; or use ACP mode |
| Docker — no agent binary | Mount binary: -v /usr/local/bin/claude:/usr/local/bin/claude; or use HTTP mode |
| Markdown not rendering | WeClaw strips markdown automatically for WeChat plain-text display; this is expected |
| Logs | tail -f ~/.weclaw/weclaw.log or docker logs -f weclaw |
Related skills
How it compares
Pick weclaw-wechat-ai-bridge over generic chatbot skills when the channel is WeChat and a Go WeClaw bridge is required, not a standard Slack or Discord webhook.
FAQ
Which AI agents does WeClaw support?
WeClaw connects WeChat to AI agents including Claude, Codex, Gemini, Kimi, and OpenClaw through a Go-based bridge that routes messages and supports OpenAI-compatible API backends.
What does weclaw-wechat-ai-bridge configure?
weclaw-wechat-ai-bridge configures WeClaw QR-code WeChat login, inbound and outbound message routing, media conversion, proactive messaging, and integration between WeChat users and agent inference backends.
When should weclaw-wechat-ai-bridge be used?
weclaw-wechat-ai-bridge should be used when a developer needs WeChat as the messaging UI for an AI agent, asks about WeClaw setup, or wants to bridge WeChat traffic to Claude or OpenAI-compatible APIs.
Is Weclaw Wechat Ai Bridge safe to install?
skills.sh reports 0 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.