Line Bot MCP Server
Featuredby
Integrates the LINE Messaging API with a Model Context Protocol server, enabling AI agents to send text, flex, broadcast messages, retrieve user profiles, and manage rich menus on a LINE Official Account.
Line Bot MCP Server Overview
What is Line Bot MCP Server about?
The project provides a Model Context Protocol (MCP) server that connects an AI agent to a LINE Official Account. It exposes a set of tools for pushing individual or broadcast messages, accessing user profiles, checking message quotas, and handling rich‑menu operations.
How to use Line Bot MCP Server?
- Create and configure a LINE Official Account and enable the Messaging API.
- Set required environment variables:
CHANNEL_ACCESS_TOKEN(long‑lived token from LINE developer console)DESTINATION_USER_ID(default recipient user ID, optional if always supplied in tool input)
- Run the server via npx:
{ "mcpServers": { "line-bot": { "command": "npx", "args": ["@line/line-bot-mcp-server"], "env": { "CHANNEL_ACCESS_TOKEN": "<YOUR_CHANNEL_ACCESS_TOKEN>", "DESTINATION_USER_ID": "<DEFAULT_USER_ID>" } } } } - The server registers tools such as
push_text_message,push_flex_message,broadcast_text_message,get_profile, etc., which can be invoked by the connected AI agent.
Key features of Line Bot MCP Server
- Message Delivery: Push single‐user text or flex messages; broadcast to all followers.
- Rich Menu Management: List, delete, set default, and cancel default rich menus.
- Profile & Quota Retrieval: Obtain user profile details and current message quota usage.
- Environment‑based Configuration: Simple setup via environment variables; supports both npx and Docker.
- Inspector Support: Run with Model Context Protocol Inspector for local debugging.
Use cases of Line Bot MCP Server
- Customer Support Automation: AI agents send personalized replies or rich flex cards directly to users on LINE.
- Marketing Campaigns: Broadcast promotional text or interactive flex messages to all followers.
- User Data Enrichment: Retrieve profile information to tailor conversations.
- Rich Menu Personalization: Dynamically change or reset rich menus based on user interactions.
- Development & Testing: Use the built‑in MCP Inspector to prototype and debug tools before deployment.
FAQ from the Line Bot MCP Server
- Do I need a paid LINE account? No, the free tier of LINE Official Accounts is sufficient for testing, but message quota limits apply.
- Can I run the server without Docker?
Yes, the preferred method is using
npx @line/line-bot-mcp-serverwith the required environment variables. - What Node.js version is required? Node.js v20 or later.
- How do I obtain
DESTINATION_USER_ID? Use the LINE Messaging API endpoint to retrieve your own user ID or set it manually if you know the target user. - Is the server production‑ready? The repository is marked as a preview version; it may lack full functionality or official support for production use.
Line Bot MCP Server's README
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. Eitheruser_idorDESTINATION_USER_IDmust 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. Eitheruser_idorDESTINATION_USER_IDmust 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 includeuser_id,DESTINATION_USER_IDis 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 toline-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 includeuser_id,DESTINATION_USER_IDis 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
Contributing
Please check CONTRIBUTING before making a contribution.
Line Bot MCP Server Reviews
Login Required
Please log in to share your review and rating for this MCP.
Actions
Line Bot MCP Server's Information
- Author
- line
- Category
- Social Media
- Language
- TypeScript
- License
- Apache License 2.0
- Version
- v0.0.1-local
- Stars
- 454
- Updated
- 1 month ago
Configuration
{
"mcpServers": {
"line-bot": {
"command": "npx",
"args": [
"@line/line-bot-mcp-server"
],
"env": {
"CHANNEL_ACCESS_TOKEN": "<YOUR_CHANNEL_ACCESS_TOKEN>",
"DESTINATION_USER_ID": "<DEFAULT_USER_ID>"
}
}
}
}Claude Code (Terminal)
claude mcp add line-bot npx @line/line-bot-mcp-serverConfigure Clients
Similar MCP Servers like Line Bot MCP Server
Explore related MCPs that share similar capabilities and solve comparable challenges
WhatsApp MCP Server
by lharries
Enables searching, reading, and sending personal WhatsApp messages and media through a Model Context Protocol (MCP) server, storing all data locally in SQLite and exposing controlled tools for LLMs like Claude.
RedNote MCP
by iFurySt
Provides authenticated access to XiaoHongShu (RedNote) notes, supporting keyword search, note retrieval by URL, and cookie persistence via a Model Context Protocol server.
Slack MCP Server
by korotovsky
Provides a powerful Model Context Protocol interface for Slack workspaces, enabling message retrieval, search, and optional posting via Stdio or SSE transports without requiring bot permissions.
YouTube MCP Server
by ZubeidHendricks
Provides a standardized interface for interacting with YouTube content, enabling video retrieval, transcript access, channel and playlist management, and advanced analytics through the Model Context Protocol.
Mcp Teams Server
by InditexTech
Provides Microsoft Teams integration via the Model Context Protocol, enabling reading, creating, replying to messages and mentioning members.
Telegram MCP Server
by chigwell
Provides a full‑featured Telegram integration for MCP‑compatible clients, enabling programmatic access to chats, messages, contacts, profile management, and group administration.
Twitter MCP
by EnesCinr
Interact with Twitter to post tweets and search tweets programmatically via an MCP server.
Meta Ads MCP
by pipeboard-co
Provides a standardized interface for AI models to retrieve performance data, visualize creatives, and manage Meta advertising campaigns across Facebook, Instagram, and other Meta platforms.
Telegram MCP Server
by chaindead
Manages Telegram dialogs, messages, drafts, and read statuses via the Model Context Protocol, enabling AI assistants to query and interact with Telegram accounts.