Content
# Gemini MCP Server with Smart Tool Intelligence
Welcome to the Gemini MCP Server, the **first MCP server with Smart Tool Intelligence** - a revolutionary self-learning system that adapts to your preferences and improves over time. This comprehensive platform provides 7 AI-powered tools with automatic prompt enhancement and context awareness.
## 🚀 Features Overview
### 🤖 7 AI-Powered Tools
- **Image Generation** - Create images from text prompts using Gemini 2.0 Flash
- **Image Editing** - Edit existing images with natural language instructions
- **Chat** - Interactive conversations with context-aware responses
- **Audio Transcription** - Convert audio to text with optional verbatim mode
- **Code Execution** - Run Python code in a secure sandbox environment
- **Video Analysis** - Analyze video content for summaries, transcripts, and insights
- **Image Analysis** - Extract objects, text, and detailed descriptions from images
### 🧠 Smart Tool Intelligence System *(First in MCP Ecosystem)*
- **Self-Learning** - Automatically learns from successful interactions
- **Context Detection** - Recognizes consciousness research, coding, debugging contexts
- **Pattern Recognition** - Identifies usage patterns and user preferences
- **Prompt Enhancement** - Refines prompts for better AI model performance
- **Persistent Memory** - Stores learned preferences across sessions
- **Automatic Migration** - Seamlessly upgrades preference storage
## 📦 Quick Start
### Installation
```bash
git clone https://github.com/Garblesnarff/gemini-mcp-server.git
cd gemini-mcp-server
npm install
```
### Configuration
1. Get your Gemini API key from [Google AI Studio](https://aistudio.google.com/app/apikey)
2. Copy the environment template:
```bash
cp .env.example .env
```
3. Edit `.env` and add your API key:
```env
GEMINI_API_KEY=your_actual_api_key_here
OUTPUT_DIR=/path/to/your/output/directory # Optional
DEBUG=false # Optional
```
### Running the Server
```bash
npm start
# or for development with debug logging:
npm run dev
```
### Integration with Claude Desktop
Add to your Claude Desktop config (`claude_desktop_config.json`):
```json
{
\"mcpServers\": {
\"gemini\": {
\"command\": \"node\",
\"args\": [\"/path/to/gemini-mcp-server/gemini-server.js\"],
\"env\": {
\"GEMINI_API_KEY\": \"your_api_key_here\"
}
}
}
}
```
## 🛠️ Tool Reference
### 1. Image Generation (`generate_image`)
Generate images from text descriptions using Gemini 2.0 Flash.
**Parameters:**
- `prompt` (string, required) - Description of the image to generate
- `context` (string, optional) - Context for Smart Tool Intelligence enhancement
**Example:**
```javascript
{
\"prompt\": \"A serene mountain landscape at sunset with vibrant colors\",
\"context\": \"artistic\"
}
```
**Returns:**
```javascript
{
\"content\": [{
\"type\": \"text\",
\"text\": \"Generated a beautiful mountain landscape image.\"
}, {
\"type\": \"image\",
\"data\": \"base64_image_data\",
\"mimeType\": \"image/png\"
}]
}
```
### 2. Image Editing (`gemini-edit-image`)
Edit existing images using natural language instructions.
**Parameters:**
- `image_path` (string, required) - Path to the image file to edit
- `edit_instruction` (string, required) - Description of desired changes
- `context` (string, optional) - Context for enhancement
**Example:**
```javascript
{
\"image_path\": \"/path/to/image.jpg\",
\"edit_instruction\": \"Add shooting stars to the night sky\",
\"context\": \"artistic\"
}
```
### 3. Chat (`gemini-chat`)
Interactive conversations with Gemini AI that learns your preferences.
**Parameters:**
- `message` (string, required) - Your message or question
- `context` (string, optional) - Context for Smart Tool Intelligence
**Example:**
```javascript
{
\"message\": \"Explain quantum computing in simple terms\",
\"context\": \"consciousness\" // Will apply academic rigor enhancement
}
```
### 4. Audio Transcription (`gemini-transcribe-audio`)
Convert audio files to text with Smart Tool Intelligence enhancement.
**Parameters:**
- `file_path` (string, required) - Path to audio file (MP3, WAV, FLAC, AAC, OGG, WEBM, M4A)
- `language` (string, optional) - Language hint for better accuracy
- `context` (string, optional) - Use \"verbatim\" for exact word-for-word transcription
- `preserve_spelled_acronyms` (boolean, optional) - Keep U-R-L instead of URL
**Example (Standard):**
```javascript
{
\"file_path\": \"/path/to/audio.mp3\",
\"language\": \"en\"
}
```
**Example (Verbatim Mode):**
```javascript
{
\"file_path\": \"/path/to/audio.mp3\",
\"context\": \"verbatim\", // Gets exact word-for-word transcription
\"preserve_spelled_acronyms\": true
}
```
**Verbatim Mode Features:**
- Captures all \"um\", \"uh\", \"like\", repeated words
- Preserves emotional expressions: [laughs], [sighs], [clears throat]
- Maintains original punctuation and sentence structure
- No summarization or cleanup
### 5. Code Execution (`gemini-code-execute`)
Execute Python code in a secure sandbox environment.
**Parameters:**
- `code` (string, required) - Python code to execute
- `context` (string, optional) - Context for enhancement
**Example:**
```javascript
{
\"code\": \"import pandas as pd\\ndata = {'x': [1,2,3], 'y': [4,5,6]}\\ndf = pd.DataFrame(data)\\nprint(df.describe())\",
\"context\": \"code\"
}
```
### 6. Video Analysis (`gemini-analyze-video`)
Analyze video content for summaries, transcripts, and detailed insights.
**Parameters:**
- `file_path` (string, required) - Path to video file (MP4, MOV, AVI, WEBM, MKV, FLV)
- `analysis_type` (string, optional) - \"summary\", \"transcript\", \"objects\", \"detailed\", \"custom\"
- `context` (string, optional) - Context for enhancement
**Example:**
```javascript
{
\"file_path\": \"/path/to/video.mp4\",
\"analysis_type\": \"detailed\"
}
```
### 7. Image Analysis (`gemini-analyze-image`)
Extract detailed information from images including objects, text, and descriptions.
**Parameters:**
- `file_path` (string, required) - Path to image file (JPEG, PNG, WebP, HEIC, HEIF, BMP, GIF)
- `analysis_type` (string, optional) - \"summary\", \"objects\", \"text\", \"detailed\", \"custom\"
- `context` (string, optional) - Context for enhancement
**Example:**
```javascript
{
\"file_path\": \"/path/to/image.jpg\",
\"analysis_type\": \"objects\"
}
```
## 🧠 Smart Tool Intelligence System
### How It Works
The Smart Tool Intelligence system is the first of its kind in the MCP ecosystem. It automatically:
1. **Detects Context** - Recognizes if you're doing consciousness research, coding, debugging, etc.
2. **Enhances Prompts** - Adds relevant instructions based on learned patterns
3. **Learns Patterns** - Stores successful interaction patterns for future use
4. **Adapts Over Time** - Gets better at helping you with each interaction
### Context Types
The system recognizes these contexts and applies appropriate enhancements:
- **`consciousness`** - Adds academic rigor, citations, detailed explanations
- **`code`** - Includes practical examples, working code, best practices
- **`debugging`** - Focuses on root cause analysis and specific fixes
- **`general`** - Applies comprehensive, structured responses
- **`verbatim`** - For audio transcription, provides exact word-for-word output
### Storage Location
Preferences are stored internally at `./data/tool-preferences.json` with automatic migration from external storage.
### Implementing Smart Tool Intelligence in Your MCP Server
Want to add this revolutionary capability to your own MCP server? Here's how:
#### 1. Core Architecture
```javascript
// src/intelligence/context-detector.js
class ContextDetector {
detectContext(prompt, toolName) {
// Implement pattern matching for different contexts
if (this.isConsciousnessContext(prompt)) return 'consciousness';
if (this.isCodeContext(prompt)) return 'code';
if (this.isDebuggingContext(prompt)) return 'debugging';
return 'general';
}
}
// src/intelligence/prompt-enhancer.js
class PromptEnhancer {
enhancePrompt(originalPrompt, context, toolName) {
// Apply context-specific enhancements
const enhancement = this.getEnhancementForContext(context);
return `${originalPrompt}\\n\\n${enhancement}`;
}
}
// src/intelligence/preference-store.js
class PreferencesManager {
async storePattern(original, enhanced, context, toolName, success) {
// Store successful patterns for future learning
}
async getPatterns(context) {
// Retrieve learned patterns for context
}
}
```
#### 2. Integration Pattern
```javascript
// In your tool's execute method:
async execute(args) {
const intelligence = IntelligenceSystem.getInstance();
// Detect context and enhance prompt
const context = args.context || intelligence.contextDetector.detectContext(args.prompt, this.name);
const enhancedPrompt = await intelligence.enhancePrompt(args.prompt, context, this.name);
// Execute with enhanced prompt
const result = await this.geminiService.generateContent(enhancedPrompt);
// Store successful pattern
await intelligence.storeSuccessfulPattern(args.prompt, enhancedPrompt, context, this.name);
return result;
}
```
#### 3. Key Implementation Files
Study these files from this repository:
- `src/intelligence/index.js` - Main intelligence coordinator
- `src/intelligence/context-detector.js` - Context recognition logic
- `src/intelligence/prompt-enhancer.js` - Enhancement application
- `src/intelligence/preference-store.js` - Pattern storage and retrieval
- `src/tools/base-tool.js` - Integration with tool execution
## 🧪 Testing
### Run Test Suite
```bash
# Test basic functionality
npm test
# Test Smart Tool Intelligence
node test-tool-intelligence-full.js
# Test internal storage
node test-internal-storage.js
# Test verbatim transcription
node test-verbatim-mode.js
```
### Manual Testing Examples
```bash
# Test image generation
echo '{\"jsonrpc\":\"2.0\",\"id\":1,\"method\":\"tools/call\",\"params\":{\"name\":\"generate_image\",\"arguments\":{\"prompt\":\"A cute robot reading a book\"}}}' | node gemini-server.js
# Test chat with consciousness context
echo '{\"jsonrpc\":\"2.0\",\"id\":2,\"method\":\"tools/call\",\"params\":{\"name\":\"gemini-chat\",\"arguments\":{\"message\":\"What is consciousness?\",\"context\":\"consciousness\"}}}' | node gemini-server.js
```
## 📊 Performance & Limits
### File Size Limits
- **Images**: 20MB (JPEG, PNG, WebP, HEIC, HEIF, BMP, GIF)
- **Audio**: 20MB (MP3, WAV, FLAC, AAC, OGG, WEBM, M4A)
- **Video**: 100MB (MP4, MOV, AVI, WEBM, MKV, FLV)
### API Rate Limits
- Follows Google Gemini API rate limits
- Built-in error handling and retry logic
- Graceful degradation on quota exceeded
## 🏗️ Architecture Deep Dive
### Modular Design
```
src/
├── server.js # MCP protocol handler
├── config.js # Configuration management
├── tools/ # Tool implementations
│ ├── index.js # Tool registry & dispatcher
│ ├── base-tool.js # Abstract base class
│ ├── chat.js # Chat tool
│ ├── image-generation.js # Image generation tool
│ ├── image-editing.js # Image editing tool
│ ├── audio-transcription.js # Audio transcription tool
│ ├── code-execution.js # Code execution tool
│ ├── video-analysis.js # Video analysis tool
│ └── image-analysis.js # Image analysis tool
├── intelligence/ # Smart Tool Intelligence
│ ├── index.js # Intelligence coordinator
│ ├── context-detector.js # Context recognition
│ ├── prompt-enhancer.js # Prompt enhancement
│ └── preference-store.js # Pattern storage
├── gemini/ # Gemini API integration
│ ├── gemini-service.js # API service layer
│ └── request-handler.js # Request formatting
└── utils/ # Utilities
├── logger.js # Logging system
└── file-utils.js # File operations
```
### Intelligence System Flow
1. **Request Received** → Tool's execute method called
2. **Context Detection** → Analyze prompt for context clues
3. **Pattern Retrieval** → Get relevant learned patterns
4. **Prompt Enhancement** → Apply context-specific improvements
5. **API Execution** → Send enhanced prompt to Gemini
6. **Pattern Storage** → Store successful interaction pattern
7. **Response Return** → Return enhanced result to user
## 🔧 Customization
### Adding New Contexts
```javascript
// In src/intelligence/context-detector.js
isMyCustomContext(prompt) {
const patterns = [
/custom pattern 1/i,
/custom pattern 2/i
];
return patterns.some(pattern => pattern.test(prompt));
}
// In src/intelligence/prompt-enhancer.js
getEnhancementForContext(context) {
const enhancements = {
'my_custom_context': 'Apply my custom enhancement instructions here.',
// ... other contexts
};
return enhancements[context] || enhancements.general;
}
```
### Adding New Tools
1. Create tool file in `src/tools/my-new-tool.js`
2. Extend `BaseTool` class
3. Implement `execute` method with intelligence integration
4. Register in `src/tools/index.js`
```javascript
// src/tools/my-new-tool.js
class MyNewTool extends BaseTool {
constructor(geminiService, intelligenceSystem) {
super('my-new-tool', 'Description of my tool', geminiService, intelligenceSystem);
}
async execute(args) {
// Use intelligence system for enhancement
const context = args.context || this.detectContext(args.input);
const enhancedPrompt = await this.enhancePrompt(args.input, context);
// Your tool logic here
const result = await this.geminiService.someMethod(enhancedPrompt);
// Store successful pattern
await this.storeSuccessfulPattern(args.input, enhancedPrompt, context);
return result;
}
}
```
## 🐛 Troubleshooting
### Common Issues
**\"Missing GEMINI_API_KEY\" Error**
```bash
# Ensure .env file exists and contains your API key
cp .env.example .env
# Edit .env and add: GEMINI_API_KEY=your_key_here
```
**\"File not found\" Errors**
```bash
# Ensure file paths are absolute and files exist
# Check file permissions and formats
```
**Intelligence System Not Learning**
```bash
# Check data directory permissions
ls -la data/
# Verify tool-preferences.json is writable
```
### Debug Mode
```bash
DEBUG=true npm start
# or
npm run dev
```
### Logs Location
- Application logs: Console output
- Intelligence patterns: `./data/tool-preferences.json`
- Generated images: `$OUTPUT_DIR` (default: `~/Claude/gemini-images`)
## 🤝 Contributing
We welcome contributions! This project represents a new paradigm in MCP server development.
### Development Setup
```bash
git clone https://github.com/Garblesnarff/gemini-mcp-server.git
cd gemini-mcp-server
npm install
npm run dev
```
### Areas for Contribution
- **New Contexts** - Add support for specialized domains
- **Enhanced Patterns** - Improve learning algorithms
- **New Tools** - Expand Gemini AI capabilities
- **Performance** - Optimize intelligence system performance
- **Documentation** - Improve guides and examples
## 📈 Roadmap
- [ ] **Multi-language Support** - Context detection in multiple languages
- [ ] **Advanced Analytics** - Usage patterns and performance metrics
- [ ] **Tool Chaining** - Intelligent coordination between multiple tools
- [ ] **Custom Models** - Support for fine-tuned Gemini models
- [ ] **Collaborative Learning** - Share anonymized patterns across instances
- [ ] **Visual Interface** - Web-based configuration and monitoring
## 🌟 Why This Matters
This is the **first MCP server that truly learns and adapts**. Traditional MCP servers are static - they do the same thing every time. Our Smart Tool Intelligence system represents a paradigm shift toward AI tools that become more helpful over time.
**For Users**: Better results with less effort as the system learns your preferences.
**For Developers**: A blueprint for building truly intelligent, adaptive AI tools.
**For the MCP Ecosystem**: A new standard for what MCP servers can become.
## 📄 License
This project is licensed under the [MIT License](LICENSE) - feel free to use, modify, and distribute.
## 🙏 Acknowledgments
Built with:
- **Google Gemini AI** - Powering the core AI capabilities
- **Model Context Protocol** - Enabling seamless integration
- **Node.js & NPM** - Runtime and package management
- **Claude & Rob** - Human-AI collaboration at its finest
---
**Ready to experience the future of MCP servers?** [Get started now](#quick-start) and watch your AI tools become smarter with every interaction! 🚀"
