mcp -templates

This MCP server instance corresponds to the legacy MCP Templates package. It provides pre-built templates to deploy common MCP servers with zero-configuration, using a CLI you can run from Python. The project historically used the mcpt CLI to list, deploy, manage, and observe template-based MCP servers. Although migration to MCP Platform is encouraged, you can still leverage the legacy templates to quickly bootstrap MCP environments. Use the included commands to list available templates, deploy a chosen template (for example 'demo' or 'filesystem'), and monitor deployments with logs. The tooling automatically discovers the tools exposed by a template and can cache template data for faster operations. Note that new features and ongoing support are now centered on MCP Platform and the mcpp CLI.

Prerequisites:

• Python 3.8+ (recommended)
• pip (comes with Python)

Install the legacy MCP Templates package:

pip install mcp-templates

Usage examples:

• List available templates:

mcpt list

• Deploy a template (example: demo):

mcpt deploy demo

• View deployment logs:

mcpt logs demo

If you need to run the server directly via Python module (legacy approach):

python -m mcp_templates

For Docker-based usage, refer to the legacy documentation for the corresponding container image and deployment commands. Migrating to MCP Platform is recommended for continued updates and feature parity.

Notes and tips:

• This repository and package represent legacy templates that have moved to MCP Platform. The recommended path is to install mcp-platform and use the mcpp CLI for new projects.
• If you are upgrading, your existing configurations generally remain compatible, but moving to MCP Platform is advised for new features and improved architecture.
• Environment variables and overrides follow the standard MCP Template conventions; refer to the legacy docs for the exact schema per template.
• If you encounter issues, check that you are invoking the correct CLI (mcpt for legacy templates, mcpp for MCP Platform) and verify Python environment paths if the command is not recognized.