Development Practices

by agentience

2 stars
1k downloads
Not rated
GitHub

About

Extracts and standardizes development practices from Git workflows, integrating with GitHub and Jira to automate branch validation, version management, and PR preparation tasks.

Details

Author
agentience
GitHub stars
2
Downloads
1,017
Categories
Productivity, Design, Workplace, Developer Tools, Automation, Communication, Infrastructure, Project Management, Other

- Validates branch names against a configured naming convention
- Creates branches following feature/, bugfix/, hotfix/, release/, and docs/ formats
- Fetches Jira issue summaries for use in branch names
- Updates Jira issue status when creating branches
- Provides both MCP tools and a CLI interface

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

  1. Download and install Highlight from highlightai.com/download
  2. Navigate to the plugins tab and select "Add Custom Plugin"
  3. Configure the plugin with the settings below
    Plugin Name Development Practices
    Command (node, npx, python, etc.) npx
    Arguments
    • Argument 1 -y
    • Argument 2 @highlight/mcp-server

    Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.

  4. Enable "Start Automatically" if you want the plugin to start when Highlight launches

From the repository

Install the package using uv, activate the virtual environment, and run the server with practices server. Use MCP tools such as validate_branch_name, create_branch, and get_branch_info, or invoke the CLI directly with commands like practices branch validate, practices branch create, and optional --update-jira or --fetch-jira flags.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "development practices": {
            "env": {},
            "args": [
                "-y",
                "@highlight/mcp-server"
            ],
            "command": "npx"
        }
    }
}

Linux

{
    "env": [],
    "args": [
        "-y",
        "@highlight/mcp-server"
    ],
    "command": "npx"
}

Macos

{
    "env": [],
    "args": [
        "-y",
        "@highlight/mcp-server"
    ],
    "command": "npx"
}

Windows

{
    "env": [],
    "args": [
        "/c",
        "npx",
        "-y",
        "@highlight/mcp-server"
    ],
    "command": "cmd"
}

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

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