home / mcp / transport department puducherry mcp server
MCP Server generated by mcp.ag2.ai
Configuration
View docs{
"mcpServers": {
"ag2-mcp-servers-transport-department-puducherry": {
"command": "python",
"args": [
"mcp_server/main.py",
"stdio"
],
"env": {
"CONFIG": "{\"example_key\":\"example_value\"}",
"SECURITY": "YOUR_SECURITY_VARS",
"CONFIG_PATH": "mcp_server/mcp_config.json"
}
}
}
}You run an MCP (Model Context Protocol) Server locally to provide programmatic access to a data source or service through a standardized interface. This makes it easier for clients to query, update, and integrate with the underlying system without needing to implement custom endpoints.
Start the MCP server in stdio mode and connect your MCP client to the local process. You don’t need to expose a remote URL for this setup; the server runs as a local subprocess and talks to your client via standard input and output. Use the environment variables to point the server at its configuration and any security credentials. When your client requests data or actions, the server translates those requests to the underlying data source and returns responses in the MCP protocol.
# Prerequisites
Python 3.9+
# Optional but recommended: install dependencies in a virtual environment
python -m venv venv
source venv/bin/activate # on Unix
venv\Scripts\activate # on Windows
# Run the MCP server directly (stdio mode)
python mcp_server/main.py stdioThe server is configured through environment variables. You can provide a path to a configuration file or pass the configuration as a JSON string. You can also supply security parameters to protect access. Typical variables include a path to a JSON config, the JSON config itself, and security-related values.
Lints and formats Python code to ensure a consistent code style and quality.
Performs static type checking to catch type errors before runtime.
Runs tests to verify behavior and prevent regressions.
Runs a suite of checks before commits to enforce quality standards.