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cc-connect-ai-bridgecc 连接 ai 桥

Agent Skill

cc-connect-ai-bridge 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

13,090

周安装

540

GitHub Stars

39

下载量

4,277
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:cc-connect-ai-bridge(cc 连接 ai 桥)
来源仓库:https://github.com/aradotso/trending-skills
仓库路径:skills/cc-connect-ai-bridge
安装命令:
npx skills add https://github.com/aradotso/trending-skills --skill cc-connect-ai-bridge
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/aradotso/trending-skills --skill cc-connect-ai-bridge

简介

cc-connect-ai-bridge 用于查找、检索和筛选相关信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词、任务场景或来源线索快速定位候选结果。
  • 通过 npm 或二进制方式安装,支持将本地 AI 代理桥接到多种消息平台。
  • 安装前建议确认权限范围和维护状态,避免触发未授权的联网或文件操作。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

CC-Connect AI Bridge

Skill by ara.so — Daily 2026 Skills collection.

CC-Connect bridges locally running AI coding agents (Claude Code, Codex, Cursor Agent, Gemini CLI, Qoder CLI, OpenCode, iFlow CLI) to messaging platforms you already use. You can chat with your local agent from Telegram, Feishu, Slack, Discord, DingTalk, WeChat Work, LINE, or QQ — no public IP required for most platforms.


Installation

Via npm (recommended)

# Stable
npm install -g cc-connect

# Beta (includes personal WeChat / Weixin ilink and other beta features)
npm install -g cc-connect@beta

Via binary

# Linux amd64
curl -L -o cc-connect https://github.com/chenhg5/cc-connect/releases/latest/download/cc-connect-linux-amd64
chmod +x cc-connect
sudo mv cc-connect /usr/local/bin/

# macOS arm64
curl -L -o cc-connect https://github.com/chenhg5/cc-connect/releases/latest/download/cc-connect-darwin-arm64
chmod +x cc-connect
sudo mv cc-connect /usr/local/bin/

Build from source (Go 1.22+)

git clone https://github.com/chenhg5/cc-connect.git
cd cc-connect
make build
# binary appears at ./bin/cc-connect

Self-update

cc-connect update          # stable
cc-connect update --pre    # beta / pre-release

Quick AI-assisted Setup

Send this prompt to Claude Code or any AI coding agent — it will install and configure cc-connect automatically:

Follow https://raw.githubusercontent.com/chenhg5/cc-connect/refs/heads/main/INSTALL.md to install and configure cc-connect.

Configuration

mkdir -p ~/.cc-connect
cp config.example.toml ~/.cc-connect/config.toml

Minimal config.toml — Claude Code + Telegram

[project.my-project]
name        = "my-project"
work_dir    = "/home/user/myproject"
data_dir    = "/home/user/.cc-connect/data"
admin_from  = "123456789"          # Your Telegram user ID

[project.my-project.agent]
type = "claude-code"               # claude-code | codex | cursor | gemini | qoder | opencode | iflow

[project.my-project.platform]
type  = "telegram"
token = "$TELEGRAM_BOT_TOKEN"      # set via env or paste value

Multi-project config

# Project 1: Claude on Telegram
[project.dev]
name     = "dev"
work_dir = "/home/user/project-a"
data_dir = "/home/user/.cc-connect/data/dev"

[project.dev.agent]
type = "claude-code"

[project.dev.platform]
type  = "telegram"
token = "$TELEGRAM_BOT_TOKEN"

# Project 2: Gemini on Feishu
[project.research]
name     = "research"
work_dir = "/home/user/project-b"
data_dir = "/home/user/.cc-connect/data/research"

[project.research.agent]
type = "gemini"

[project.research.platform]
type           = "feishu"
app_id         = "$FEISHU_APP_ID"
app_secret     = "$FEISHU_APP_SECRET"
verification_token = "$FEISHU_VERIFICATION_TOKEN"

All supported platform types

type valuePlatformPublic IP needed?
telegramTelegramNo (long polling)
feishuFeishu / LarkNo (WebSocket)
dingtalkDingTalkNo (Stream)
slackSlackNo (Socket Mode)
discordDiscordNo (Gateway)
wecomWeChat WorkNo (WS) / Yes (Webhook)
lineLINEYes (Webhook)
qqQQ via NapCat/OneBotNo
qqbotQQ Bot OfficialNo
weixinPersonal WeChat (beta)No (ilink long polling)

All supported agent types

type valueAgent
claude-codeClaude Code (Anthropic)
codexCodex (OpenAI)
cursorCursor Agent
geminiGemini CLI (Google)
qoderQoder CLI
opencodeOpenCode / Crush
iflowiFlow CLI

Platform-specific configuration

Telegram

[project.mybot.platform]
type  = "telegram"
token = "$TELEGRAM_BOT_TOKEN"
# Get token from @BotFather on Telegram
# No public IP required — uses long polling

Feishu / Lark

[project.mybot.platform]
type               = "feishu"
app_id             = "$FEISHU_APP_ID"
app_secret         = "$FEISHU_APP_SECRET"
verification_token = "$FEISHU_VERIFICATION_TOKEN"
# Uses WebSocket — no public IP needed
# Set up at https://open.feishu.cn/

Slack

[project.mybot.platform]
type              = "slack"
bot_token         = "$SLACK_BOT_TOKEN"
app_token         = "$SLACK_APP_TOKEN"
# app_token must start with xapp- (Socket Mode)
# Enable Socket Mode in your Slack app settings

Discord

[project.mybot.platform]
type  = "discord"
token = "$DISCORD_BOT_TOKEN"
# Uses Discord Gateway — no public IP needed

DingTalk

[project.mybot.platform]
type       = "dingtalk"
client_id  = "$DINGTALK_CLIENT_ID"
client_secret = "$DINGTALK_CLIENT_SECRET"
# Uses DingTalk Stream — no public IP needed

WeChat Work (WeCom)

[project.mybot.platform]
type           = "wecom"
corp_id        = "$WECOM_CORP_ID"
agent_id       = "$WECOM_AGENT_ID"
secret         = "$WECOM_SECRET"
connection_type = "websocket"   # websocket (no public IP) or webhook

Personal WeChat (beta only)

# Install beta build first
npm install -g cc-connect@beta

# Scan QR code to log in
cc-connect weixin setup
[project.mybot.platform]
type = "weixin"
# Auth state is stored after QR scan — no public IP needed

Running cc-connect

# Default config location: ~/.cc-connect/config.toml
cc-connect

# Custom config path
cc-connect --config /path/to/config.toml

# Run specific project only
cc-connect --project my-project

Chat Commands (sent in the messaging platform)

CommandDescription
/helpShow all available commands
/model <name>Switch AI model (e.g. /model claude-opus-4-5)
/mode <mode>Change permission mode (e.g. /mode auto)
/reasoning <level>Tune reasoning intensity
/dir <path>Switch working directory for next session
/dir <number>Jump to a directory from history
/dir -Toggle to previous directory
/dir resetRestore configured work_dir
/cd <path>Alias for /dir
/memoryRead or write the agent's memory/instruction file
/shell <cmd>Run a shell command (admin only)
/sessionManage sessions (list, continue, new)
/continueContinue from last session (forks to avoid inheriting broken state)
/cron <spec> <task>Schedule a recurring task
/stopStop the currently running agent

Slash command examples (in chat)

# Ask the agent to review a PR
Review the changes in branch feature/auth and summarize the risks.

# Switch to a different model
/model gemini-2.0-flash

# Change working directory
/dir /home/user/other-project

# Schedule a daily summary
/cron 0 6 * * * Summarize GitHub trending Go repos and post here

# Read agent memory
/memory

# Update agent memory
/memory Always prefer table-driven tests in Go. Use context.Context for cancellation.

Multi-Agent Relay (group chat orchestration)

Bind multiple bots in one group chat so they communicate with each other:

# Bot 1: Claude
[project.claude-bot]
name     = "claude-bot"
work_dir = "/home/user/project"
data_dir = "/home/user/.cc-connect/data/claude"

[project.claude-bot.agent]
type = "claude-code"

[project.claude-bot.platform]
type  = "telegram"
token = "$TELEGRAM_CLAUDE_BOT_TOKEN"

# Bot 2: Gemini (same group)
[project.gemini-bot]
name     = "gemini-bot"
work_dir = "/home/user/project"
data_dir = "/home/user/.cc-connect/data/gemini"

[project.gemini-bot.agent]
type = "gemini"

[project.gemini-bot.platform]
type  = "telegram"
token = "$TELEGRAM_GEMINI_BOT_TOKEN"

Add both bots to the same Telegram group. Mention them by name and they will pick up and respond to each other's output.


Voice and Multimodal

For platforms that support voice (Telegram, Feishu, DingTalk), enable speech in config:

[speech]
provider = "openai"           # openai | azure | google
api_key  = "$OPENAI_API_KEY"

[speech.stt]
model = "whisper-1"

[speech.tts]
model = "tts-1"
voice = "alloy"

Send a voice message in Telegram → cc-connect transcribes it → forwards text to the agent → optionally speaks the response back.

For images/screenshots: just attach the image in chat. cc-connect forwards it to multimodal-capable agents.


Cron Scheduling

# In config.toml, per-project cron settings
[project.mybot.cron]
timeout = "30m"          # max runtime per job
fresh_session = true     # start a new session for each run

From chat:

# Every weekday at 9am, run a standup summary
/cron 0 9 * * 1-5 Summarize open PRs and blockers in this repo

# Every hour, check for new issues labeled "urgent"
/cron 0 * * * * Check for new GitHub issues labeled urgent and notify me

Admin configuration

[project.mybot]
admin_from = "alice,123456789"   # comma-separated usernames or IDs

Admins can use /shell, /dir, and other privileged commands. Non-admins cannot.


Directory structure

~/.cc-connect/
├── config.toml                          # main config
└── data/
    └── projects/
        └── my-project.state.json        # persisted dir override, session state

Common patterns

Pattern 1: Mobile-first AI development

Install cc-connect on your dev machine, connect it to Telegram. From your phone:

  1. Send a task description as a message
  2. Agent runs on your machine
  3. Streamed response appears in chat
  4. Reply to continue the conversation

Pattern 2: Team shared AI bot (Slack/Feishu)

One cc-connect instance per project, shared in a team channel. Team members can ask questions, trigger code reviews, or run analyses — all without terminal access.

Pattern 3: Scheduled reports

/cron 0 8 * * 1 Generate a weekly summary of commits and open issues, format as markdown

Pattern 4: Multi-project routing

Run multiple projects in one cc-connect process, each bot handles a different repo or concern.


Troubleshooting

Bot not responding

  1. Check that cc-connect is running: ps aux | grep cc-connect
  2. Verify the platform token/credentials in config
  3. For Telegram: ensure the bot token is valid (/start in BotFather chat)
  4. For Feishu: check WebSocket connection in Feishu Open Platform console

Agent not found

# Verify agent is installed and in PATH
which claude     # for claude-code
which gemini     # for gemini
which codex      # for codex

Set explicit path in config if needed:

[project.mybot.agent]
type = "claude-code"
bin  = "/usr/local/bin/claude"

Session inherits broken state

Use /continue which forks the session, or start fresh:

/session new

Personal WeChat not available

You need the beta build:

npm install -g cc-connect@beta
cc-connect weixin setup   # scan QR in terminal

Context too long / auto-compress

Enable in config:

[project.mybot.agent]
auto_compress        = true
compress_threshold   = 80000   # tokens before compression kicks in

Config not found

Default path is ~/.cc-connect/config.toml. Pass explicitly:

cc-connect --config /custom/path/config.toml

Check version

cc-connect --version

Environment variables reference

VariableUsed for
TELEGRAM_BOT_TOKENTelegram bot token
FEISHU_APP_IDFeishu app ID
FEISHU_APP_SECRETFeishu app secret
FEISHU_VERIFICATION_TOKENFeishu verification token
SLACK_BOT_TOKENSlack bot OAuth token (xoxb-...)
SLACK_APP_TOKENSlack app-level token (xapp-...)
DISCORD_BOT_TOKENDiscord bot token
DINGTALK_CLIENT_IDDingTalk app client ID
DINGTALK_CLIENT_SECRETDingTalk app client secret
WECOM_CORP_IDWeChat Work corp ID
WECOM_AGENT_IDWeChat Work agent ID
WECOM_SECRETWeChat Work app secret
OPENAI_API_KEYOpenAI API key (for Codex agent or STT/TTS)

Values in config.toml can reference env vars using $VAR_NAME syntax.


Platform setup guides

  • Feishu/Lark: docs/feishu.md
  • DingTalk: docs/dingtalk.md
  • Telegram: docs/telegram.md
  • Slack: docs/slack.md
  • Discord: docs/discord.md
  • WeChat Work: docs/wecom.md
  • Personal WeChat (beta): docs/weixin.md
  • QQ / QQ Bot: docs/qq.md

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

35.91%
按下载量换算1,536

Claude

29.42%
按下载量换算1,258

Cursor

19.4%
按下载量换算830

Gemini CLI

11.13%
按下载量换算476

安全审计

Gen Agent Trust Hub

未通过

Socket

可疑

Snyk

可疑

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/aradotso/trending-skills --skill cc-connect-ai-bridge 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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