cc-connect
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.
Best use case
cc-connect is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
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.
Teams using cc-connect should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/cc-connect/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How cc-connect Compares
| Feature / Agent | cc-connect | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
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.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# 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
```bash
npm install -g cc-connect
```
### Configuration
Create a `cc-connect.yaml` in your project:
```yaml
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
```bash
cc-connect init # Interactive wizard for platform credentials
cc-connect start # Start routing messages
```
### Session Management
```yaml
session:
timeout: 30m
max_concurrent: 3
continue: true
auto_compress: true
```
### Multi-Agent Routing
Route different commands to different agents:
```yaml
agents:
code-review:
type: claude-code
workdir: /path/to/project
trigger: "!review"
research:
type: gemini
trigger: "!research"
```
### Access Control
```yaml
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:
```yaml
# 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:
```yaml
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](https://github.com/chenhg5/cc-connect) for full documentationRelated Skills
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