CCM
/MCP
SkillsMCPMarketplacesDigestLearnAdvertise

This week in Claude

Every Monday: Claude Code, Agent SDK, MCP, and the Anthropic platform moves worth your time.

Skills by Category
Frontend DevelopmentBackend & APIsTesting & QASecurityDevOps & CI/CDGit & Pull RequestsDocumentationCode Review & QualityAI & Agent BuildingSkill Development
MCP Servers by Category
Sales & MarketingWeb & Browser AutomationDatabasesAI & LLM ToolsCloud & InfrastructureCommunication & MessagingDeveloper ToolsDesign & CreativeDocuments & KnowledgeSearch & Web Crawling
Marketplaces by Category
AI Agents & OrchestrationLLM IntegrationDevelopment ToolsFrontend & UIBackend & APIsDatabasesTesting & Code QualityDevOps & CloudSecurity & ComplianceGit & Version Control

Claude Code Marketplaces

Discover Claude Code plugins, extensions, and tools. Automatically updated directory of Anthropic Claude AI marketplaces with development tools, productivity plugins, and integrations.

Resources

  • Browse Skills
  • Browse MCP Servers
  • Browse Marketplaces
  • Plugins Reference

Community

  • About
  • Learn
  • Feedback
  • Privacy Policy
  • Advertise

Built for the Claude Code community with Claude Code by @mertduzgun

Independent project, not affiliated with Anthropic

LINE Bot

line/line-bot-mcp-server
583
Summary

The LINE Bot MCP Server integrates the LINE Messaging API to enable AI agents to interact with LINE Official Accounts through six primary tools: pushing text or customizable flex messages to individual users, broadcasting messages to all followers, retrieving user profile information, and managing account resources like message quotas and rich menus. It solves the problem of connecting AI agents to the LINE messaging platform by providing a standardized MCP interface for sending messages, accessing user data, and managing account-level messaging features.

CodeRabbit
CodeRabbit
AI writes the code. CodeRabbit catches the slop.
Try For Free →
Make your agent a DeFi expert
Make your agent a DeFi expert
Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →
Make money from your Skills
Make money from your Skills
On Capafy, your Skill runs online 24/7 as an agent product, and you get paid every time someone uses it.
Start earning →
AppSignal
AppSignal
Monitor with ease. Code with confidence.
Start Free Trial →
Vibe Prospecting MCPVibe Prospecting MCP
Vibe Prospecting MCP
Connect Claude to +800M contacts, +150M companies. Find & Enrich leads in chat.
Try For Free →
Context.devContext.dev
Context.dev
Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →
CodeRabbit
CodeRabbit
AI writes the code. CodeRabbit catches the slop.
Try For Free →
Make your agent a DeFi expert
Make your agent a DeFi expert
Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →
Make money from your Skills
Make money from your Skills
On Capafy, your Skill runs online 24/7 as an agent product, and you get paid every time someone uses it.
Start earning →
AppSignal
AppSignal
Monitor with ease. Code with confidence.
Start Free Trial →
Vibe Prospecting MCPVibe Prospecting MCP
Vibe Prospecting MCP
Connect Claude to +800M contacts, +150M companies. Find & Enrich leads in chat.
Try For Free →
Context.devContext.dev
Context.dev
Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →

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.

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.

Featured
CodeRabbit
CodeRabbit
AI writes the code. CodeRabbit catches the slop.
Try For Free →
Make your agent a DeFi expert
Make your agent a DeFi expert
Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →
Make money from your Skills
Make money from your Skills
On Capafy, your Skill runs online 24/7 as an agent product, and you get paid every time someone uses it.
Start earning →
AppSignal
AppSignal
Monitor with ease. Code with confidence.
Start Free Trial →
Vibe Prospecting MCPVibe Prospecting MCP
Vibe Prospecting MCP
Connect Claude to +800M contacts, +150M companies. Find & Enrich leads in chat.
Try For Free →
Context.devContext.dev
Context.dev
Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →
Categories
AI & LLM ToolsCommunication & Messaging
UpdatedDec 15, 2025
View on GitHub

Related AI & LLM Tools MCP Servers

View all →
SkillFM LLM Cost Optimizer

io.github.ericm1018/skillfm-llm-cost-optimizer-openai-anthropic-usage

LLM cost optimizer for OpenAI, Anthropic, token usage, BYOK, and SkillFM Beacon audits.
Llm Orchestration Agent

io.github.mikerawsonnz/llm-orchestration-agent

Run a prompt through a LangChain (system + human) chain over Gemini on Vertex AI; optional LangSmith
Authenticated Llm Agent

io.github.mikerawsonnz/authenticated-llm-agent

JWT-gated LLM gateway: authenticate (bcrypt/JWT), then run a LangChain-on-Vertex Gemini completion.
Copilot Memory MCP

labforgedev/copilot-memory-mcp

Persistent semantic memory for AI agents using local ChromaDB vector search. No cloud required.
1
Agent Prompt Injection Firewall Mcp

csoai-org/agent-prompt-injection-firewall-mcp

The WAF for agents. Pattern-based + heuristic firewall scans prompts, RAG documents, tool argume...
Authenticated Multi Llm Agent

io.github.mikerawsonnz/authenticated-multi-llm-agent

Google-OAuth-gated LLM gateway: verify a Google ID token, then run a Gemini (Vertex AI) completion f