cc-connect

name cc-connect description Bridge local AI coding agents (Claude Code, Cursor, Gemini CLI, Codex) to messaging platforms (Slack, Telegram, Discord). Use when: controlling AI agents from team chat, sending coding tasks via Slack/Telegram, building team-accessible AI workflows. license MIT compatibility Node.js 18+ or Python 3.10+ metadata {"author":"terminal-skills","version":"1.0.0","category":"automation","tags":["ai-agents","messaging","slack","telegram","bridge"]} 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: "xoxb-8234567890-..." 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