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:
     • userId (string?): The user ID to receive a message. Defaults to DESTINATION_USER_ID. Either userId 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:
     • userId (string?): The user ID to receive a message. Defaults to DESTINATION_USER_ID. Either userId or DESTINATION_USER_ID must be set.
     • message.altText (string): Alternative text shown when flex message cannot be displayed.
     • message.contents (any): The contents 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.contents (any): The contents 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:
     • userId (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

11. create_rich_menu

    • Create a rich menu based on the given actions. Generate and upload an image. Set as default.
    • Inputs:
      • chatBarText (string): Text displayed in chat bar, also used as rich menu name.
      • actions (array): The actions of the rich menu. You can specify minimum 1 to maximum 6 actions. Each action can be one of the following types:
        • postback: For sending a postback action
        • message: For sending a text message
        • uri: For opening a URL
        • datetimepicker: For opening a date/time picker
        • camera: For opening the camera
        • cameraRoll: For opening the camera roll
        • location: For sending the current location
        • richmenuswitch: For switching to another rich menu
        • clipboard: For copying text to clipboard

12. get_follower_ids

    • Get a list of user IDs of users who have added the LINE Official Account as a friend. This allows you to obtain user IDs for sending messages without manually preparing them.
    • Inputs:
      • start (string?): Continuation token to get the next array of user IDs. Returned in the next property of a previous response.
      • limit (number?): The maximum number of user IDs to retrieve in a single request.

13. get_group_summary

    • Get the group chat summary including group ID, group name, and group icon URL, using the group ID.
    • Inputs:
      • groupId (string): The group ID of the target group chat.

Installation (Using npx)

requirements:

• Node.js v22 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 userId, DESTINATION_USER_ID is required. You can confirm this by following this instructions.

jsonCopy code
{
  "mcpServers": {
    "line-bot": {
      "command": "npx",
      "args": [
        "@line/line-bot-mcp-server"
      ],
      "env": {
        "NPM_CONFIG_IGNORE_SCRIPTS": "true",
        "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:

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

Build the Docker image:

Copy code
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 userId, DESTINATION_USER_ID is required. You can confirm this by following this instructions.

jsonCopy code
{
  "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:

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

2. Install dependencies:

bashCopy code
npm install

3. Build the project:

bashCopy code
npm run build

Run the Inspector

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

bashCopy code
npx @modelcontextprotocol/inspector node dist/index.js \
  -e CHANNEL_ACCESS_TOKEN="YOUR_CHANNEL_ACCESS_TOKEN" \
  -e DESTINATION_USER_ID="YOUR_DESTINATION_USER_ID"

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.