MCP Server Practices

An MCP server that provides tools and resources for development practices.

Features

Branch Management

The Practices MCP server provides tools for managing Git branches according to a standardized convention:

• feature/PMS-123-brief-description: Feature branches for new features (from develop)
• bugfix/PMS-123-brief-description: Bug fix branches (from develop)
• hotfix/1.0.1-brief-description: Hot fix branches for urgent fixes (from main)
• release/1.1.0: Release branches for preparing releases (from develop)
• docs/update-readme: Documentation branches (from develop)

Via MCP Tools

The server provides the following MCP tools:

1. validate_branch_name: Validates a branch name against the configured convention
2. create_branch: Creates a new branch following the convention
3. get_branch_info: Gets information about a branch

Example:

from mcp.tools import call_tool

# Validate a branch name
result = call_tool(
    "practices", 
    "validate_branch_name", 
    {"branch_name": "feature/PMS-123-add-authentication"}
)

# Create a branch
result = call_tool(
    "practices", 
    "create_branch", 
    {
        "branch_type": "feature",
        "identifier": "PMS-123",
        "description": "add-authentication",
        "update_jira": True
    }
)

# Get branch info
result = call_tool(
    "practices", 
    "get_branch_info", 
    {"branch_name": "feature/PMS-123-add-authentication"}
)

Via CLI

The package also provides a command-line interface:

# Validate a branch name
practices branch validate feature/PMS-123-add-authentication

# Create a branch
practices branch create feature PMS-123 add authentication

# Create a branch and update Jira status
practices branch create feature PMS-123 add authentication --update-jira

# Create a branch using Jira summary as description
practices branch create feature PMS-123 --fetch-jira

Integration with Jira

The server integrates with Jira to:

1. Fetch issue summaries for use in branch names
2. Update issue status when creating branches

Installation

1. Clone the repository

2. Create a virtual environment with uv:

   uv venv
   source .venv/bin/activate
   

3. Install the package in development mode:

   uv pip install -e .
   

   Note: If you encounter issues with the mcp-python-sdk dependency, you may need to install it separately or use a workaround specific to your environment.

Running the Server

# Activate the virtual environment
source .venv/bin/activate

# Run the MCP server
practices server

Development

1. Create a virtual environment and install the package as described above
2. Install development dependencies:

   uv pip install -e ".[dev]"
   

3. Run tests:

   # With the virtual environment activated
   PYTHONPATH=./src python -m unittest discover tests
   

License

MIT