MCP Prompt Collector
Tools for logging, analyzing, and improving Claude Desktop prompts to enhance prompt engineering skills.
MCP Prompt Collector
An MCP server that provides interactive tools for logging, analyzing, and improving your Claude Desktop prompts to help you develop better prompt engineering skills.
Installation
Option 1: NPM Package (Recommended)
# Install globally
npm install -g mcp-prompt-collector
# Or install locally in your project
npm install mcp-prompt-collector
Option 2: From Source
git clone https://github.com/daneb/improver-mcp.git
cd improver-mcp
npm install
npm run build
Setup
-
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
What It Does
- 🛠️ Interactive Tools: Provides 4 tools accessible in Claude Desktop for prompt analysis
- 📊 Quality Analysis: Scores prompts on structure, clarity, context, and effectiveness
- 💡 Smart Insights: Identifies patterns and suggests specific improvements
- 📈 Progress Tracking: Shows quality trends and improvement over time
- 🌐 Web Dashboard: Clean interface to view history, analytics, and insights
Features
Core Functionality
- ✅ Interactive MCP tools for Claude Desktop integration
- ✅ SQLite database for local storage (no cloud sync)
- ✅ Real-time prompt quality scoring
- ✅ Web dashboard with analytics
- ✅ Automated insights generation
Available Tools
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 trends
Analysis Engine
- Quality Scoring: 0-10 score based on structure, clarity, and completeness
- Complexity Detection: Categorizes prompts as simple, moderate, or complex
- Technique Suggestions: Recommends optimal prompting techniques
- Issue Detection: Identifies ambiguity, missing context, bias, etc.
Dashboard Features
- Prompt history with search and filtering
- Quality trends over time
- Complexity distribution charts
- Recent activity overview
- Actionable improvement insights
Usage
In Claude Desktop
Once 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
Development Commands
# 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
How It Works
- MCP Integration: Registers as an MCP server with Claude Desktop
- Interactive Tools: Provides 4 tools accessible through Claude Desktop interface
- Manual Logging: Users explicitly log prompts using the
log_prompttool - Analysis: Scores quality, detects patterns, identifies improvements
- Storage: Saves everything locally in SQLite database
- Insights: Generates personalized suggestions based on your patterns
- Dashboard: Provides web interface to view analytics and history
Configuration
Default 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
}
}
Data Storage
All data is stored locally in SQLite database:
- Location:
~/.mcp-prompt-collector/data/prompt_history.db - Privacy: No cloud sync, complete local control
- Retention: Configurable cleanup after N days
- Export: Full data export capabilities
Development
# 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
Architecture
- MCP Protocol Handler: Communicates with Claude Desktop
- Storage Manager: SQLite database operations
- Analysis Engine: Prompt quality scoring and insights
- Dashboard Server: Express.js web interface
- Background Worker: Scheduled analysis and cleanup
Privacy & Security
- ✅ Local Only: All data stays on your machine
- ✅ No Cloud Sync: Zero external data transmission
- ✅ User Control: Complete data ownership and export
- ✅ Transparent: Open source, auditable code
Requirements
- Node.js: 18+
- Claude Desktop: Latest version with MCP support
- macOS: Primary support (Windows/Linux coming soon)
Troubleshooting
Server won't start
- Check if port 3456 is available
- Verify Claude Desktop MCP configuration
- Run
mcp-prompt-collector statusfor diagnostics
No prompts showing in dashboard
- Make sure you're using the
log_prompttool in Claude Desktop - Prompts are not automatically captured - you must manually log them
- Check that the MCP server tools are available in Claude Desktop
Dashboard not loading
- Check if server is running on correct port
- Try different port with
setup --port 3457 - Check browser console for errors
License
MIT License - see LICENSE file for details
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