Which integrations are available for this server?

Provides access to LINE Bot messages through webhook events, enabling reading and analysis of LINE conversations with support for text, sticker, and image messages stored in JSON format.

How do I use Python LINE MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Python LINE MCP Server show me recent text messages from the LINE group chat" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

Python LINE MCP Server

Version Python MCP FastAPI License

A Model Context Protocol server implementation in Python that provides access to LINE Bot messages. This server enables Language Models to read and analyze LINE conversations through a standardized interface.

Features

Core Functionality

Asynchronous operation using Python's asyncio
Environment-based configuration using python-dotenv
Comprehensive logging system
LINE Bot webhook event handling
Message storage in JSON format
FastAPI integration for API endpoints
Pydantic models for data validation
Support for text, sticker, and image messages

Prerequisites

Python 3.8+
Required Python packages:
- fastapi
- pydantic
- python-dotenv
- mcp-server
- line-bot-sdk
- uvicorn

Installation

git clone https://github.com/amornpan/py-mcp-line.git cd py-mcp-line pip install -r requirements.txt

Project Structure

PY-MCP-LINE/ ├── src/ │ └── line/ │ ├── __init__.py │ └── server.py ├── data/ │ └── messages.json ├── tests/ │ ├── __init__.py │ └── test_line.py ├── .env ├── .env.example ├── .gitignore ├── README.md ├── Dockerfile └── requirements.txt

Directory Structure Explanation

src/line/ - Main source code directory
- __init__.py - Package initialization
- server.py - Main server implementation
data/ - Data storage directory
- messages.json - Stored LINE messages
tests/ - Test files directory
- __init__.py - Test package initialization
- test_line.py - LINE functionality tests
.env - Environment configuration file (not in git)
.env.example - Example environment configuration
.gitignore - Git ignore rules
README.md - Project documentation
Dockerfile - Docker configuration
requirements.txt - Project dependencies

Configuration

Create a .env file in the project root:

LINE_CHANNEL_SECRET=your_channel_secret LINE_ACCESS_TOKEN=your_access_token SERVER_PORT=8000 MESSAGES_FILE=data/messages.json

API Implementation Details

Resource Listing

@app.list_resources() async def list_resources() -> list[Resource]

Lists available message types from the LINE Bot
Returns resources with URIs in the format line://<message_type>/data
Includes resource descriptions and MIME types

Resource Reading

@app.read_resource() async def read_resource(uri: AnyUrl) -> str

Reads messages of the specified type
Accepts URIs in the format line://<message_type>/data
Returns messages in JSON format
Supports filtering by date, user, or content

Usage with Claude Desktop

Add to your Claude Desktop configuration:

On MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json On Windows: %APPDATA%/Claude/claude_desktop_config.json

{ "mcpServers": { "line": { "command": "python", "args": [ "server.py" ], "env": { "LINE_CHANNEL_SECRET": "your_channel_secret", "LINE_ACCESS_TOKEN": "your_access_token", "SERVER_PORT": "8000", "MESSAGES_FILE": "data/messages.json" } } } }