Tools for logging, analyzing, and improving Claude Desktop prompts to enhance prompt engineering skills.
An MCP server that provides interactive tools for logging, analyzing, and improving your Claude Desktop prompts to help you develop better prompt engineering skills.
# Install globally
npm install -g mcp-prompt-collector
# Or install locally in your project
npm install mcp-prompt-collector
git clone https://github.com/daneb/improver-mcp.git
cd improver-mcp
npm install
npm run build
Configure Claude Desktop
Add this to your ~/Library/Application Support/Claude/claude_desktop_config.json
:
For global npm install:
{
"mcpServers": {
"mcp-prompt-collector": {
"command": "mcp-prompt-collector",
"env": {
"HOME": "/Users/daneb"
}
}
}
}
For source installation:
{
"mcpServers": {
"mcp-prompt-collector": {
"command": "/path/to/your/node",
"args": ["/path/to/improver-mcp/dist/index.js"],
"env": {
"HOME": "/Users/daneb"
}
}
}
}
Restart Claude Desktop to load the MCP server
Access the dashboard at http://localhost:3456
log_prompt
- Log and analyze a prompt with immediate quality feedbackimprove_prompt
- Get specific suggestions for improving any promptget_prompt_insights
- View analytics and patterns from your prompt historyview_stats
- Display comprehensive statistics and quality trendsOnce the MCP server is running, you'll have access to these tools in Claude Desktop:
log_prompt
- Use: Log and analyze any prompt
- Example: "log_prompt" with your prompt text
- Returns: Quality score, complexity, and improvement suggestions
improve_prompt
- Use: Get specific suggestions for a prompt
- Example: "improve_prompt" with your prompt and optional goal
- Returns: Detailed analysis and actionable improvement recommendations
get_prompt_insights
- Use: View patterns and insights from your prompt history
- Example: "get_prompt_insights" optionally filtered by category
- Returns: Analytics on your prompting patterns and common issues
view_stats
- Use: See comprehensive statistics and trends
- Example: "view_stats" for last 30 days (configurable)
- Returns: Total prompts, quality trends, complexity breakdown
# Build and run
npm run build # Build TypeScript
npm run dev # Development mode with auto-reload
npm start # Start the MCP server
# Code quality
npm test # Run tests
npm run lint # Check code style
npm run format # Format code
log_prompt
toolDefault configuration is stored in ~/.mcp-prompt-collector/config/settings.json
:
{
"name": "mcp-prompt-collector",
"capabilities": {
"intercept": true,
"modify": false,
"store": true
},
"settings": {
"enhancePrompts": false,
"storageLocation": "~/.mcp-prompt-collector/data",
"dashboardPort": 3456,
"analysisLevel": "detailed",
"retentionDays": 90
}
}
All data is stored locally in SQLite database:
~/.mcp-prompt-collector/data/prompt_history.db
# Clone and setup
git clone <repo-url>
cd mcp-prompt-collector
npm install
# Development workflow
npm run dev # Watch mode
npm run build # Production build
npm test # Run tests
npm run lint # Code quality
# Testing
npm run test:unit # Unit tests
npm run test:integration # Integration tests
Server won't start
mcp-prompt-collector status
for diagnosticsNo prompts showing in dashboard
log_prompt
tool in Claude DesktopDashboard not loading
setup --port 3457
MIT License - see LICENSE file for details
Provides LLM access to the Cucumber Studio testing platform for managing and executing tests.
Provides multi-cluster Kubernetes management and operations using MCP, featuring a management interface, logging, and nearly 50 built-in tools covering common DevOps and development scenarios. Supports both standard and CRD resources.
A proxy server that combines multiple MCP servers into a single endpoint, routing requests to the appropriate underlying server.
Flag features, manage company data, and control feature access using Bucket.
A template project demonstrating interaction between a TypeScript-based MCP server and a Unity client.
Manipulate Adventure Game Studio (AGS) compiled room (.crm) files to enable AI-powered game development.
MCP Server for automated reverse engineering with IDA Pro.
Interact with various build systems including Gradle, Maven, NPM/Yarn, Cargo, Python, Makefile, and CMake.
Enables IDEs like Cursor and Windsurf to analyze large codebases using Gemini's 1M context window.
Provides API documentation from Apifox projects as a data source for AI programming tools that support MCP.