Line Bot MCP Server

What is Line Bot MCP Server about?

The server acts as a bridge between an AI agent (e.g., Claude Desktop, Cline) and a LINE Official Account, exposing a set of tools that let the agent push text or flex messages, broadcast to all followers, retrieve user profiles, manage message quotas, and handle rich menus.

How to use Line Bot MCP Server?

1. Create and configure a LINE Official Account and enable the Messaging API.
2. Provide required environment variables:
   • CHANNEL_ACCESS_TOKEN – long‑lived token for your LINE channel.
   • DESTINATION_USER_ID – default recipient ID (optional, but needed if the tool call does not supply user_id).
3. Run the server via npx (or Docker) as shown in the configuration example.
4. Within your AI agent’s configuration, reference the MCP server under mcpServers so the agent can invoke the exposed tools.

Key features of Line Bot MCP Server

• Push Text Message – send simple text to a specified user.
• Push Flex Message – send rich, customizable Flex JSON layouts.
• Broadcast Text / Flex – deliver messages to all followers of the official account.
• Get Profile – retrieve user display name, picture, status message, and language.
• Message Quota – query monthly quota and usage.
• Rich Menu Management – list, delete, set default, or cancel default rich menus.
• Node.js & Docker support – easy local development with the MCP Inspector.

Use cases of Line Bot MCP Server

• Customer support bots that proactively send updates or answer queries via LINE.
• Marketing campaigns broadcasting promotional Flex messages to all followers.
• Personal assistants delivering daily summaries or reminders to a user’s LINE chat.
• Content management where an AI curates and pushes rich media (menus, carousels) to a brand’s LINE channel.
• Analytics dashboards that monitor message quota and usage in real time.

FAQ from the Line Bot MCP Server

Q: Do I need to install anything besides Node.js? A: No. With Node.js v20+ you can run the server directly using npx @line/line-bot-mcp-server.

Q: Can I run the server without a Docker container? A: Yes. The recommended approach is the npx command; Docker is optional for isolated environments.

Q: What happens if I omit DESTINATION_USER_ID? A: The tool will require a user_id in each call; otherwise it will return an error indicating the missing default recipient.

Q: Are there limits on the number of messages I can send? A: The get_message_quota tool shows your monthly quota and current consumption as defined by LINE’s Messaging API limits.

Q: How do I debug tools locally? A: Use the MCP Inspector: npx @modelcontextprotocol/inspector node dist/index.js to interactively test each tool.

日本語版 READMEはこちら

LINE Bot MCP Server

Model Context Protocol (MCP) server implementation that integrates the LINE Messaging API to connect an AI Agent to the LINE Official Account.

[!NOTE] This repository is provided as a preview version. While we offer it for experimental purposes, please be aware that it may not include complete functionality or comprehensive support.

Tools

1. push_text_message
   • Push a simple text message to a user via LINE.
   • Inputs:
     • user_id (string?): The user ID to receive a message. Defaults to DESTINATION_USER_ID. Either user_id or DESTINATION_USER_ID must be set.
     • message.text (string): The plain text content to send to the user.
2. push_flex_message
   • Push a highly customizable flex message to a user via LINE.
   • Inputs:
     • user_id (string?): The user ID to receive a message. Defaults to DESTINATION_USER_ID. Either user_id or DESTINATION_USER_ID must be set.
     • message.altText (string): Alternative text shown when flex message cannot be displayed.
     • message.content (any): The content of the flex message. This is a JSON object that defines the layout and components of the message.
     • message.contents.type (enum): Type of the container. 'bubble' for single container, 'carousel' for multiple swipeable bubbles.
3. broadcast_text_message
   • Broadcast a simple text message via LINE to all users who have followed your LINE Official Account.
   • Inputs:
     • message.text (string): The plain text content to send to the users.
4. broadcast_flex_message
   • Broadcast a highly customizable flex message via LINE to all users who have added your LINE Official Account.
   • Inputs:
     • message.altText (string): Alternative text shown when flex message cannot be displayed.
     • message.content (any): The content of the flex message. This is a JSON object that defines the layout and components of the message.
     • message.contents.type (enum): Type of the container. 'bubble' for single container, 'carousel' for multiple swipeable bubbles.
5. get_profile
   • Get detailed profile information of a LINE user including display name, profile picture URL, status message and language.
   • Inputs:
     • user_id (string?): The ID of the user whose profile you want to retrieve. Defaults to DESTINATION_USER_ID.
6. get_message_quota
   • Get the message quota and consumption of the LINE Official Account. This shows the monthly message limit and current usage.
   • Inputs:
     • None
7. get_rich_menu_list
   • Get the list of rich menus associated with your LINE Official Account.
   • Inputs:
     • None
8. delete_rich_menu
   • Delete a rich menu from your LINE Official Account.
   • Inputs:
     • richMenuId (string): The ID of the rich menu to delete.
9. set_rich_menu_default
   • Set a rich menu as the default rich menu.
   • Inputs:
     • richMenuId (string): The ID of the rich menu to set as default.
10. cancel_rich_menu_default
    • Cancel the default rich menu.
    • Inputs:
      • None

Installation (Using npx)

requirements:

• Node.js v20 or later

Step 1: Create LINE Official Account

This MCP server utilizes a LINE Official Account. If you do not have one, please create it by following this instructions.

If you have a LINE Official Account, enable the Messaging API for your LINE Official Account by following this instructions.

Step 2: Configure AI Agent

Please add the following configuration for an AI Agent like Claude Desktop or Cline.

Set the environment variables or arguments as follows:

• CHANNEL_ACCESS_TOKEN: (required) Channel Access Token. You can confirm this by following this instructions.
• DESTINATION_USER_ID: (optional) The default user ID of the recipient. If the Tool's input does not include user_id, DESTINATION_USER_ID is required. You can confirm this by following this instructions.

{
  "mcpServers": {
    "line-bot": {
      "command": "npx",
      "args": [
        "@line/line-bot-mcp-server"
      ],
      "env": {
        "CHANNEL_ACCESS_TOKEN" : "FILL_HERE",
        "DESTINATION_USER_ID" : "FILL_HERE"
      }
    }
  }
}

Installation (Using Docker)

Step 1: Create LINE Official Account

This MCP server utilizes a LINE Official Account. If you do not have one, please create it by following this instructions.

If you have a LINE Official Account, enable the Messaging API for your LINE Official Account by following this instructions.

Step 2: Build line-bot-mcp-server image

Clone this repository:

git clone git@github.com:line/line-bot-mcp-server.git

Build the Docker image:

docker build -t line/line-bot-mcp-server .

Step 3: Configure AI Agent

Please add the following configuration for an AI Agent like Claude Desktop or Cline.

Set the environment variables or arguments as follows:

• mcpServers.args: (required) The path to line-bot-mcp-server.
• CHANNEL_ACCESS_TOKEN: (required) Channel Access Token. You can confirm this by following this instructions.
• DESTINATION_USER_ID: (optional) The default user ID of the recipient. If the Tool's input does not include user_id, DESTINATION_USER_ID is required. You can confirm this by following this instructions.

{
  "mcpServers": {
    "line-bot": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "CHANNEL_ACCESS_TOKEN",
        "-e",
        "DESTINATION_USER_ID",
        "line/line-bot-mcp-server"
      ],
      "env": {
        "CHANNEL_ACCESS_TOKEN" : "FILL_HERE",
        "DESTINATION_USER_ID" : "FILL_HERE"
      }
    }
  }
}

Local Development with Inspector

You can use the MCP Inspector to test and debug the server locally.

Prerequisites

1. Clone the repository:

git clone git@github.com:line/line-bot-mcp-server.git
cd line-bot-mcp-server

2. Install dependencies:

npm install

3. Build the project:

npm run build

Run the Inspector

After building the project, you can start the MCP Inspector:

npx @modelcontextprotocol/inspector node dist/index.js

This will start the MCP Inspector interface where you can interact with the LINE Bot MCP Server tools and test their functionality.

Versioning

This project respects semantic versioning

See http://semver.org/

Contributing

Please check CONTRIBUTING before making a contribution.