Imported from terminalskills/skills (skills/cc-connect/SKILL.md). Install upstream with npx skills add terminalskills/skills --skill cc-connect. Copyright stays with the author (MIT).

CC-Connect

Overview

CC-Connect bridges AI coding agents running on your local machine to the messaging platforms your team already uses. Code review, research, automation, data analysis — anything an AI agent can do, now accessible from your phone, tablet, or any device with a chat app.

Architecture: Your local AI agent <-> CC-Connect bridge <-> Messaging platform (Slack/Telegram/Discord/etc.)

Send a message in Slack, CC-Connect routes it to your local Claude Code instance, the agent does the work, and the response comes back to your chat.

Instructions

Installation

npm install -g cc-connect

Configuration

Create a cc-connect.yaml in your project:

agent:
  type: claude-code  # or: codex, gemini, cursor
  workdir: /path/to/your/project

platform:
  type: telegram  # or: slack, discord, feishu, dingtalk
  token: "your-bot-token"

Platform Setup

Telegram: Create a bot via @BotFather, get the bot token, and add it to your config.

Slack: Create a Slack App at api.slack.com/apps, enable Socket Mode and Event Subscriptions, add Bot Token Scopes (chat:write, app_mentions:read, messages.im), and install to your workspace.

Discord: Create an application at discord.com/developers, create a bot, enable Message Content Intent, and invite the bot to your server.

Starting the Bridge

cc-connect init    # Interactive wizard for platform credentials
cc-connect start   # Start routing messages

Session Management

session:
  timeout: 30m
  max_concurrent: 3
  continue: true
  auto_compress: true

Multi-Agent Routing

Route different commands to different agents:

agents:
  code-review:
    type: claude-code
    workdir: /path/to/project
    trigger: "!review"
  research:
    type: gemini
    trigger: "!research"

Access Control

access:
  allowed_users: ["U123", "U456"]
  allowed_channels: ["C789"]
  admin_users: ["U123"]

Examples

Example 1: Team Code Review via Slack

A team sets up CC-Connect to allow engineers to request code reviews from Slack:

# cc-connect.yaml
agent:
  type: claude-code
  workdir: /home/dev/acme-api

platform:
  type: slack
  app_token: "xapp-1-A07QX4R..."
  bot_token: "[REDACTED slack-token]-..."
  channels: ["#code-review"]

session:
  timeout: 10m
  auto_compress: true

access:
  allowed_channels: ["#code-review"]
  allowed_users: ["U0381KDLS", "U0492JFMA"]

In Slack #code-review, an engineer types: @agent Review the auth module for SQL injection risks. Claude Code analyzes the code and responds in the thread with findings.

Example 2: Scheduled Daily Reports via Telegram

A solo developer configures CC-Connect with cron jobs for automated daily standup reports:

agent:
  type: claude-code
  workdir: /home/dev/saas-app

platform:
  type: telegram
  token: "7284619035:AAF-kLm9xPqR..."
  allowed_users: ["198274563"]

cron:
  - schedule: "0 9 * * 1-5"
    command: "Summarize yesterday's git commits and open PRs, highlight blockers"
    platform: telegram
    timeout: 5m
    fresh_session: true

Every weekday at 9am, the agent generates a summary of recent activity and sends it to the developer's Telegram chat.

Guidelines

• Start with one messaging platform and get it working before expanding to others
• Always set allowed_users in production to restrict access
• Use threads in Slack/Discord to keep conversations organized
• Set session.timeout to prevent runaway agent sessions consuming resources
• Enable auto_compress for long conversations to prevent context overflow
• Use fresh_session: true for cron jobs to avoid inherited context from previous runs
• Verify your setup with cc-connect status if messages are not routing
• See the GitHub Repository for full documentation