WHAT IT CONNECTS
What py-mcp-line gives an AI Agent
The source catalog does not include a structured feature list. Review the repository documentation before use.
SECURITY
An MCP listing is not a security review
An MCP server may receive model context, credentials, local files, or permission to call external systems. Review its code, requested environment variables, network behavior, package provenance, and maintenance status before connecting it to an agent.
README
Repository documentation
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.
- 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
- Python 3.8+
- Required Python packages:
- fastapi
- pydantic
- python-dotenv
- mcp-server
- line-bot-sdk
- uvicorn
git clone https://github.com/amornpan/py-mcp-line.git
cd py-mcp-line
pip install -r requirements.txtPY-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
src/line/- Main source code directory__init__.py- Package initializationserver.py- Main server implementation
data/- Data storage directorymessages.json- Stored LINE messages
tests/- Test files directory__init__.py- Test package initializationtest_line.py- LINE functionality tests
.env- Environment configuration file (not in git).env.example- Example environment configuration.gitignore- Git ignore rulesREADME.md- Project documentationDockerfile- Docker configurationrequirements.txt- Project dependencies
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@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
@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
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"
}
}
}
}The server implements comprehensive error handling for:
- Webhook validation failures
- Message storage errors
- Resource access errors
- URI validation
- LINE API response errors
All errors are logged and returned with appropriate error messages.
- Environment variable based configuration
- LINE message signature validation
- Proper error handling
- Input validation through Pydantic
Feel free to reach out to me if you have any questions about this project or would like to collaborate!
Made with ❤️ by Amornpan Phornchaicharoen
Amornpan Phornchaicharoen
Create a requirements.txt file with:
fastapi>=0.104.1
pydantic>=2.10.6
uvicorn>=0.34.0
python-dotenv>=1.0.1
line-bot-sdk>=3.5.0
anyio>=4.5.0
mcp==1.2.0
These versions have been tested and verified to work together. The key components are:
fastapianduvicornfor the API serverpydanticfor data validationline-bot-sdkfor LINE Bot integrationmcpfor Model Context Protocol implementationpython-dotenvfor environment configurationanyiofor asynchronous I/O support
- LINE Developers for the LINE Messaging API
- Model Context Protocol community
- Python FastAPI community
- Contributors to the python-dotenv project
COMMUNITY