agent-kakaotalk

Automate KakaoTalk chat reading, listing, and messaging via CLI.

170|25|Updated Jan 30, 2026
One-click install
npx skills add https://github.com/agent-messenger/agent-messenger --skill agent-kakaotalk
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: agent-kakaotalk
Source: https://github.com/agent-messenger/agent-messenger/tree/main/skills/agent-kakaotalk
Command: npx skills add https://github.com/agent-messenger/agent-messenger --skill agent-kakaotalk

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Interact with KakaoTalk programmatically to enable AI agents to read chats, list conversations, and send messages without manual login.

Core Features & Use Cases

  • Credential extraction from KakaoTalk desktop app and login flow to securely authenticate AI agents.
  • List chats, read messages, and send messages across multiple accounts and devices.
  • Supports per-chat and per-account commands, JSON output by default, and integration with templates and references.

Quick Start

Tell the AI to log in to KakaoTalk, list chats, and send a message to a target chat.

Frequently Asked Questions about agent-kakaotalk

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate KakaoTalk message sending from a CLI?

You can automate KakaoTalk message sending by using a CLI to authenticate, list chat conversations, and issue per-chat message commands. This allows AI agents to programmatically send messages without manual desktop interaction.

Can I manage multiple KakaoTalk accounts with a single CLI?

Yes, you can manage multiple KakaoTalk accounts using a single CLI across platforms. The system supports per-account command sets, allowing AI agents to switch contexts and manage distinct conversations independently.

How does authentication work for KakaoTalk automation?

Authentication works by extracting credentials from the KakaoTalk desktop app and executing an auth login flow. This securely authenticates AI agents, enabling them to programmatically access chat lists and send messages.

What is the default output format when reading chats and listing conversations?

The default output format for reading chats and listing conversations is JSON. This structured output allows AI agents to easily parse chat data, manage message payloads, and integrate with referenced templates.

Does KakaoTalk automation work across different platforms?

Yes, KakaoTalk automation works across platforms via a single CLI interface. It enables AI agents to execute authentication workflows, read chats, and send messages consistently regardless of the operating system.

Are there limitations when extracting credentials from the KakaoTalk desktop app?

Credential extraction requires access to the KakaoTalk desktop app to initiate the auth login flow. Limitations include dependency on the desktop environment for initial setup before AI agents can automate messaging and chat management.