Development Practices
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
- License
- MIT license
Explore
- 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:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Development PracticesCommand (node, npx, python, etc.)npxArguments-
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.
-
Argument 1
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
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.
source .venv/bin/activate
PYTHONPATH=./src python -m unittest discover tests
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:
```python
from mcp.tools import call_tool
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"
}
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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