LINE Bot MCP Server
[日本語版 READMEはこちら](README.ja.md)
# LINE Bot MCP Server
[](https://www.npmjs.com/package/@line/line-bot-mcp-server)
[Model Context Protocol (MCP)](https://github.com/modelcontextprotocol) 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](https://developers.line.biz/en/docs/messaging-api/getting-started/#create-oa).
If you have a LINE Official Account, enable the Messaging API for your LINE Official Account by following [this instructions](https://developers.line.biz/en/docs/messaging-api/getting-started/#using-oa-manager).
### 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](https://developers.line.biz/en/docs/basics/channel-access-token/#long-lived-channel-access-token).
- `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](https://developers.line.biz/en/docs/messaging-api/getting-user-ids/#get-own-user-id).
```json
{
"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](https://developers.line.biz/en/docs/messaging-api/getting-started/#create-oa).
If you have a LINE Official Account, enable the Messaging API for your LINE Official Account by following [this instructions](https://developers.line.biz/en/docs/messaging-api/getting-started/#using-oa-manager).
### 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](https://developers.line.biz/en/docs/basics/channel-access-token/#long-lived-channel-access-token).
- `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](https://developers.line.biz/en/docs/messaging-api/getting-user-ids/#get-own-user-id).
```json
{
"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:
```bash
git clone git@github.com:line/line-bot-mcp-server.git
cd line-bot-mcp-server
```
2. Install dependencies:
```bash
npm install
```
3. Build the project:
```bash
npm run build
```
### Run the Inspector
After building the project, you can start the MCP Inspector:
```bash
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](./CONTRIBUTING.md) before making a contribution.
TDQS
Scored across 18 tools
There is significant overlap between broadcast/push variants (e.g., broadcast_text_message vs broadcast_messages vs broadcast_flex_message) and between Gemini-integrated tools (gemini_command vs push_gemini_flex vs push_gemini_text vs ai_query_mssql), which could lead to confusion about which tool to use for similar tasks. However, the descriptions help clarify some distinctions, such as between generic and specific message types.
Most tools follow a consistent snake_case verb_noun pattern (e.g., broadcast_text_message, get_profile, delete_rich_menu), with clear actions like broadcast, push, get, set, delete, query, and export. Minor deviations include ai_query_mssql (starts with 'ai_') and gemini_command (uses 'command' instead of a more specific verb), but overall the naming is predictable and readable.
With 18 tools, the count feels borderline heavy for a LINE bot server, as it includes many overlapping or specialized variants (e.g., multiple broadcast and push tools). While the scope covers messaging, user management, rich menus, and database queries, the set could be streamlined without losing functionality, making it slightly overwhelming for an agent to navigate.
The tool surface provides good coverage for LINE bot operations, including messaging (broadcast/push with text/flex), user profile retrieval, rich menu management (list/set/cancel/delete), and database queries (MSSQL with AI integration). Minor gaps include lack of tools for updating user data or handling webhook events, but core workflows are well-supported, allowing agents to perform essential tasks without major dead ends.