Sandbox
@line/line-bot-mcp-server

MCP server for LINE Messaging API and Official Account

LINE Bot MCP Server is an MCP connector that gives an agent access to the LINE Messaging API. It can push and broadcast text or flex messages, fetch profiles and quotas, manage rich menus, and list followers or group summaries. You configure it with a LINE channel access token and, optionally, a default destination user ID, then add it to your MCP client as a server.

775 stars150 forksTypeScriptUpdated 6d ago
Who it's for

Builders who want their agent to send messages and manage LINE Official Accounts from an MCP client.

What it delivers

You can have an agent send LINE messages and manage account data without switching tools.

What it does

Send LINE messages

`push_text_message`, `push_flex_message`, `broadcast_text_message`, and `broadcast_flex_message` send direct or broadcast messages through the LINE Messaging API.

Read account and user data

`get_profile`, `get_message_quota`, `get_follower_ids`, and `get_group_summary` pull profile, quota, follower, and group details.

Manage rich menus

`get_rich_menu_list`, `delete_rich_menu`, `set_rich_menu_default`, `cancel_rich_menu_default`, and `create_rich_menu` handle rich menu setup and changes.

Create rich menus from actions

`create_rich_menu` builds a menu from actions like postback, message, uri, datetimepicker, camera, cameraRoll, location, richmenuswitch, and clipboard.

Run as MCP server

The server is packaged for MCP clients such as Claude Desktop or Cline, with npx and Docker setup examples in the README.

How to get it

  1. 1Clone this repository
    git clone git@github.com:line/line-bot-mcp-server.git
  2. 2Build the Docker image
    docker build -t line/line-bot-mcp-server .

README

日本語版 READMEはこちら

LINE Bot MCP Server

npmjs

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.
{
  "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:

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 userId, 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
  1. Install dependencies:
npm install
  1. 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 \
  -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.

Files in the repo

Repository payload23 top-level entries
  • .github
  • assets
  • richmenu-template
  • scripts
  • src
  • test
  • .editorconfig
  • .gitignore
  • .npmrc
  • .prettierrc.json
  • CODE_OF_CONDUCT.md
  • CONTRIBUTING.md
  • Dockerfile
  • LICENSE
  • manifest.json
  • package-lock.json
  • package.json
  • README.ja.md
  • README.md
  • renovate.json5
  • tsconfig.json
  • tsconfig.test.json
  • vitest.config.ts

Discussion (0)

Ask about usage, or say what you built with it

Sign in to join the discussion.

No comments yet. Be the first to say what this is good for.

More connectors

Real-time global intelligence dashboard. AI-powered news aggregation, geopolitical monitoring, and infrastructure tracking in a unified situational awareness interface

86k

High-performance code intelligence MCP server. Indexes codebases into a persistent knowledge graph — average repo in milliseconds. 158 languages, sub-ms queries, 99% fewer tokens. Single static binary, zero dependencies.

43k

Universal provider proxy for OpenAI Codex & Claude Code — use any LLM (Claude, Gemini, Grok, DeepSeek, Ollama…) with Codex CLI, App, SDK, and Claude Code

14k
okf-memory/
okf-agent-memory

Git-native persistent memory for AI coding agents. Implements Google OKF v0.2 with sub-300µs in-memory BM25 search, embedded MCP server, and progressive disclosure. Slashes token bloat by 80% with zero external databases or dependencies. Built in pure Go.

547
tirth8205/
code-review-graph

Local-first code intelligence graph for MCP and CLI. Builds a persistent map of your codebase so AI coding tools read only what matters, with benchmarked context reductions on reviews and large-repo workflows.

31k
2akouwu/
reverify

Stop your AI from making things up — it proposes, deterministic tools decide, every claim checked against ground truth with evidence. Grounded facts and context survive resets. Reverse engineering is the proving ground. MCP server + CLI.

1.1k