MCP Prompt Enhancer
A Model Context Protocol (MCP) server for intelligent prompt preprocessing with adaptive context management.
Overview
The MCP Prompt Enhancer intelligently analyzes your codebase and enhances LLM prompts with relevant context to produce higher quality AI responses. It features:
- Two-tier Context System: Initial full project analysis combined with task-focused context tracking
- Adaptive Context Intelligence: Only provides relevant context based on the current task
- Context Caching: Reuses analyzed project information instead of reprocessing
- Task Detection: Automatically infers task type from prompts (page creation, debugging, refactoring, etc.)
- Git Integration: Includes recent changes and commit history when relevant
- Framework Detection: Auto-detects React, Vue, Next.js, etc. and includes relevant patterns
Installation
# Install globally
npm install -g mcp-prompt-enhancer
# Or install in your project
npm install --save-dev mcp-prompt-enhancer
Quick Start
The MCP Prompt Enhancer now uses STDIO for communication instead of a network server:
# Process a prompt enhancement request
echo '{"action":"enhance_prompt","params":{"prompt":"Fix errors in the app.js file","taskType":"debugging"}}' | node dist/index.js
# Refresh project context
echo '{"action":"set_project_context","params":{"forceRefresh":true}}' | node dist/index.js
The server analyzes the current directory by default and responds with JSON output.
Usage with Claude
The MCP Prompt Enhancer now uses STDIO for communication, making it easier to integrate with Claude. This approach eliminates network dependencies and simplifies the integration process.
Using with Claude
To use the MCP Prompt Enhancer with Claude:
- Start the server in a background process:
- Send JSON requests to the server via STDIO:
echo '{"action":"enhance_prompt","params":{"prompt":"Create a new React component for user profile","taskType":"creation"}}' | node dist/index.js
- Parse the JSON response to extract the enhanced prompt.
Claude Integration Example
Here's how to integrate with Claude using a wrapper script:
// claude-mcp-enhancer.js
const { spawn } = require('child_process');
const path = require('path');
async function enhancePrompt(prompt, options = {}) {
return new Promise((resolve, reject) => {
const serverPath = path.join(__dirname, 'dist/index.js');
const server = spawn('node', [serverPath]);
let output = '';
server.stdout.on('data', (data) => {
output += data.toString();
});
server.stderr.on('data', (data) => {
console.error(`Server error: ${data}`);
});
server.on('close', (code) => {
if (code !== 0) {
reject(new Error(`Server exited with code ${code}`));
return;
}
try {
// Find and parse JSON in the output
const jsonStart = output.indexOf('{');
if (jsonStart >= 0) {
const jsonStr = output.substring(jsonStart);
const result = JSON.parse(jsonStr);
resolve(result);
} else {
reject(new Error('No valid JSON found in server output'));
}
} catch (error) {
reject(error);
}
});
// Prepare request
const request = {
action: 'enhance_prompt',
params: {
prompt,
...options
}
};
// Send request to server
server.stdin.write(JSON.stringify(request) + '\n');
server.stdin.end();
});
}
// Example usage:
// enhancePrompt("Fix the bug in the login form", { taskType: "debugging" })
// .then(result => console.log(result.data.enhancedPrompt))
// .catch(error => console.error(error));
module.exports = { enhancePrompt };
This wrapper can be used to integrate the MCP Prompt Enhancer with Claude or any other system.
API
STDIO JSON Protocol
The server accepts JSON requests via standard input and responds with JSON via standard output.
{
"action": "action_name",
"params": {
// Action-specific parameters
}
}
{
"status": "success|error",
"data": {
// Response data (for success)
},
"error": "Error message (for error)"
}
Available Actions
enhance_prompt
Enhances a prompt with relevant project context.
Request Parameters:
{
"action": "enhance_prompt",
"params": {
"prompt": "Your original prompt here",
"taskType": "debugging", // Optional
"focusFiles": ["path/to/file"], // Optional
"includeFullContext": false // Optional
}
}
Response (Success):
{
"status": "success",
"data": {
"enhancedPrompt": "# Context Information\n\n...\n\n# Original Prompt\n\nYour original prompt here",
"taskType": "debugging",
"focusArea": "backend",
"contextAdded": true,
"contextSize": 250
}
}
set_project_context
Manually refreshes or sets the project context.
Request Parameters:
{
"action": "set_project_context",
"params": {
"projectPath": "/path/to/project", // Optional
"forceRefresh": true // Optional
}
}
Response (Success):
{
"status": "success",
"data": {
"message": "Project context updated for project-name",
"projectName": "project-name",
"frameworks": ["react", "express"],
"timestamp": "2025-07-10T05:44:24.521Z"
}
}
Configuration
Create a mcp-prompt-enhancer.config.js file in your project root:
module.exports = {
contextCacheTTL: 900, // 15 minutes in seconds
maxContextSize: 10000, // Maximum tokens for context
ignorePatterns: ['node_modules', 'dist', '.git', 'build', 'coverage', '*.log'],
logLevel: 'info' // 'debug', 'info', 'warn', 'error'
};
You can also use environment variables:
MCP_LOG_LEVEL: Set the logging level
How It Works
- Project Analysis: Scans your project structure, detects frameworks, and extracts key patterns
- Task Detection: Analyzes prompts to determine the type of work being done
- Context Selection: Intelligently selects relevant files and information based on the task
- Prompt Enhancement: Combines the original prompt with targeted context
- Continuous Learning: Updates its understanding as you work on different parts of the codebase
See the architecture diagram for a detailed visual representation of how the MCP Prompt Enhancer works with Cline (Anthropic's CLI for Claude).
Development
# Clone the repository
git clone https://github.com/yourusername/mcp-prompt-enhancer.git
cd mcp-prompt-enhancer
# Install dependencies
npm install
# Build the project
npm run build
# Run tests
npm test
# Start in development mode
npm run dev
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
License
This project is licensed under the MIT License - see the LICENSE file for details.