Project Customization MCP
Generates and maintains project-specific instructions for GitHub Copilot to guide code suggestions and development practices.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Project Customization MCP Analyze my project and generate customization guidelines."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Project Customization MCP
An open-source MCP (Model Context Protocol) server that automates project customization by analyzing your codebase and generating AI-ready configuration files based on industry best practices. Perfect for teams and individual developers who want consistent, framework-aware project guidelines.
Platform-agnostic: Works with any IDE, editor, or AI tool that supports the Model Context Protocol (VS Code, JetBrains, Cursor, Claude, etc.)
What You Get
This tool automatically:
π Analyzes your project - Detects frameworks, languages, and project structure
π Generates guidelines - Creates
.github/copilot-instructions.mdfor consistent developmentβοΈ Updates documentation - Enhances README with best practices
π‘ Provides recommendations - Suggests improvements for your codebase
Related MCP server: devflow-mcp
π― Tools Available
π
analyze_project- Scan your project and detect frameworks/languagesπ
generate_copilot_instructions- Create customization guidelines for your projectπ
update_readme- Generate or enhance README with standardsπ
get_customization_recommendations- Get actionable improvement suggestions
π Resources Available
π¦ Project Metadata - Your project type, frameworks, languages
π Project Structure - Directory organization and files
π Current Guidelines - Existing customization files
π README - Your current documentation
π¬ Prompts Available
β‘
analyze-and-customize- Full workflow (analyze β generate β update)β¨
generate-instructions-only- Create just the instruction fileπ
review-and-improve- Review existing customizations
π¦ Installation
βοΈ Option 1: Using npx (Recommended - No Installation Needed)
{
"mcpServers": {
"project-customization": {
"command": "npx",
"args": ["-y", "project-customization-mcp"]
}
}
}π Option 2: Global npm Installation
npm install -g project-customization-mcpThen configure:
{
"mcpServers": {
"project-customization": {
"command": "project-customization-mcp",
"env": {
"MCP_API_KEY": "YOUR_KEY"
}
}
}
}π Authorization (Tools Only)
Tool execution requires an API key configured via MCP_API_KEY in the MCP server configuration env. If the key is missing, tool calls return an authorization error. Prompts and resources remain available without any key.
Example configuration:
{
"mcpServers": {
"project-customization": {
"command": "project-customization-mcp",
"env": {
"MCP_API_KEY": "YOUR_KEY"
}
}
}
}π§ Memory (GitHub Copilot Hosted)
This MCP server does not store memory. Use GitHub Copilot's hosted memory feature for long-lived context, per GitHub's Copilot memory documentation.
π How to Use
1οΈβ£ Configure in Your IDE
VS Code:
Ctrl+Shift+Pβ "MCP: Open User Configuration"Cursor: Settings β MCP Servers
Other IDEs: Refer to your IDE's MCP documentation
Add one of the configurations above and restart your IDE.
2οΈβ£ Use in Chat
Open your chat and type:
Analyze my project and set up customization based on best practicesOr use specific prompts:
/analyze-and-customize
/generate-instructions-only
/review-and-improve3. Add Resources to Chat
Add project context:
Select "Add Context" β "MCP Resources"
Choose: Project Metadata, Project Structure, Guidelines, README
π What Gets Generated
The tool creates or updates:
β
.github/copilot-instructions.md- Project-specific guidelines and standardsβ
README.md- Enhanced with setup and development guidelinesβ Recommendations - Suggestions for framework-specific improvements
π Example Output
For a React TypeScript project, you get:
# Project Guidelines
## Code Style
- Use functional components with hooks
- Maintain strict TypeScript (no `any`)
- ESLint + Prettier for formatting
## Project Structure
- src/components - React components
- src/pages - Page components
- src/utils - Utilities
- src/hooks - Custom hooksπ License
MIT License - See LICENSE file
π Made for the Model Context Protocol | Works with any MCP-compatible client
Available Tools
4 toolsanalyze_projectB
Analyze a VS Code project structure and detect project type, frameworks, languages, and customization opportunities
Inputs: projectPath.
generate_copilot_instructionsC
Generate a .github/copilot-instructions.md file based on project analysis and best practices
Inputs: projectPath, analysisData.
get_customization_recommendationsC
Get recommendations for customizing VS Code settings, instruction files, and project guidelines
Inputs: projectPath, analysisData.
update_readmeC
Update or create README.md with project guidelines and best practices
Inputs: guidelines, projectPath, analysisData.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelogβ¦
TDQS
Scored across 4 tools
analyze_project and get_customization_recommendations both surface customization opportunities, creating some overlap. However, generate_copilot_instructions and update_readme clearly target distinct output files, and the descriptions help distinguish the intended use cases.
All four tools use consistent snake_case verb_noun naming: analyze_project, generate_copilot_instructions, update_readme, and get_customization_recommendations. The verbs are clear and the pattern is predictable throughout.
Four tools is well-scoped for a project customization utility, covering analysis, generation, updating, and recommendations without bloat or excessive thinness. Each tool has a distinct role in the workflow.
The surface covers analysis, copilot instruction generation, README updates, and recommendations, but there is no tool to actually create or update VS Code settings or extensions files. This leaves a notable dead end for the settings-customization part of the stated purpose.
Maintenance
Related MCP Connectors
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An MCP server that gives your AI access to the source code and docs of all public github repos
MCP server for generating rough-draft project plans from natural-language prompts.
MCP server for building and testing AI agents with multi-model experimentation and insights.
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