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

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.
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.
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.
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.
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.
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
get_rich_menu_list
- Get the list of rich menus associated with your LINE Official Account.
- Inputs:
  - None
delete_rich_menu
- Delete a rich menu from your LINE Official Account.
- Inputs:
  - richMenuId (string): The ID of the rich menu to delete.
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.
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

Clone the repository:

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

Install dependencies:

npm install

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.

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

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.
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.
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.
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.
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.
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
get_rich_menu_list
- Get the list of rich menus associated with your LINE Official Account.
- Inputs:
  - None
delete_rich_menu
- Delete a rich menu from your LINE Official Account.
- Inputs:
  - richMenuId (string): The ID of the rich menu to delete.
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.
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

Clone the repository:

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

Install dependencies:

npm install

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.