Skill Detail

Bridge local coding agents into chat apps with cc-connect

Let operators control local Claude Code, Codex, Cursor, Gemini CLI, and other coding agents from Slack, Discord, Telegram, Feishu/Lark, DingTalk, LINE, and WeChat Work.

Integrations & ConnectorsMulti-Framework
Integrations & Connectors Multi-Framework Security Reviewed
⭐ 14.2k GitHub stars ⬇ 17.2k/wk npm
INSTALL WITH ANY AGENT
npx skills add agentskillexchange/skills --skill bridge-local-coding-agents-into-chat-apps-with-cc-connect Copy
Works best when you want a reusable capability, not another fragile one-off prompt.
At a glance
Tools required
Node.js/npm or Homebrew, a supported local coding-agent CLI, and at least one supported chat platform account or bot
Install & setup
Install with npm install -g cc-connect or brew install cc-connect, run cc-connect web to configure projects, providers, and platforms, then start cc-connect for the bridge service.
Author
chenhg5
Publisher
Individual
Last updated
Jul 19, 2026
Quick brief

Use cc-connect when an operator needs to keep a local coding agent reachable from team or mobile chat without exposing the workstation directly. The workflow is to install the bridge, bind one or more local agent CLIs to project directories, connect approved messaging platforms, and let the operator inspect code, run commands, troubleshoot, or continue a coding session from chat. This is not a generic chat bot card: the boundary is remote control of local AI coding agents through configured messaging adapters, project bindings, admin controls, and platform-specific setup guides.

How it works

What this skill actually does

Inputs and prerequisites: Node.js/npm or Homebrew, a supported local coding-agent CLI, and at least one supported chat platform account or bot.

Setup notes: Install with npm install -g cc-connect or brew install cc-connect, run cc-connect web to configure projects, providers, and platforms, then start cc-connect for the bridge service.

Source and verification boundary: use https://github.com/chenhg5/cc-connect as the canonical reference before running the workflow; keep commands, API calls, CLI usage, and generated outputs reviewable against that upstream source.

Framework fit: publish this as a Multi-Framework workflow only when the operator can invoke the documented toolchain directly, rather than treating the upstream project as a generic product listing.