MCP Server Gemini

Instructions

Implementation Reference

• src/enhanced-stdio-server.ts:1158-1284 (handler)

  The getHelp method is the main handler for the 'get_help' tool. It takes a topic parameter and returns the corresponding help content as an MCP response.

    private getHelp(id: any, args: any): MCPResponse {
      const topic = args?.topic || 'overview';
      let helpContent = '';
  
      switch (topic) {
        case 'overview':
          helpContent = this.getHelpContent('overview');
          break;
  
        case 'tools':
          helpContent = this.getHelpContent('tools');
          break;
  
        case 'models':
          helpContent = `# Available Gemini Models
  
  ## Thinking Models (Latest - 2.5 Series)
  **gemini-2.5-pro**
  - Most capable, best for complex reasoning
  - 2M token context window
  - Features: thinking, JSON mode, grounding, system instructions
  
  **gemini-2.5-flash** ⭐ Recommended
  - Best balance of speed and capability
  - 1M token context window
  - Features: thinking, JSON mode, grounding, system instructions
  
  **gemini-2.5-flash-lite**
  - Ultra-fast, cost-efficient
  - 1M token context window
  - Features: thinking, JSON mode, system instructions
  
  ## Standard Models (2.0 Series)
  **gemini-2.0-flash**
  - Fast and efficient
  - 1M token context window
  - Features: JSON mode, grounding, system instructions
  
  **gemini-2.0-flash-lite**
  - Most cost-efficient
  - 1M token context window
  - Features: JSON mode, system instructions
  
  **gemini-2.0-pro-experimental**
  - Excellent for coding
  - 2M token context window
  - Features: JSON mode, grounding, system instructions
  
  ## Model Selection Guide
  - Complex reasoning: gemini-2.5-pro
  - General use: gemini-2.5-flash
  - Fast responses: gemini-2.5-flash-lite
  - Cost-sensitive: gemini-2.0-flash-lite
  - Coding tasks: gemini-2.0-pro-experimental`;
          break;
  
        case 'parameters':
          helpContent = this.getHelpContent('parameters');
          break;
  
        case 'examples':
          helpContent = this.getHelpContent('examples');
          break;
  
        case 'quick-start':
          helpContent = `# Quick Start Guide
  
  ## 1. Basic Usage
  Just ask naturally:
  - "Use Gemini to [your request]"
  - "Ask Gemini about [topic]"
  
  ## 2. Common Tasks
  
  **Text Generation:**
  "Use Gemini to write a function that sorts arrays"
  
  **Image Analysis:**
  "What's in this image?" [attach image]
  
  **Model Info:**
  "List all Gemini models"
  
  **Token Counting:**
  "Count tokens for my prompt"
  
  ## 3. Advanced Features
  
  **JSON Output:**
  "Use Gemini in JSON mode to extract key points"
  
  **Current Information:**
  "Use Gemini with grounding to get latest news"
  
  **Conversations:**
  "Start a chat with Gemini about Python"
  
  ## 4. Tips
  - Use gemini-2.5-flash for most tasks
  - Lower temperature for facts, higher for creativity
  - Enable grounding for current information
  - Use conversation IDs to maintain context
  
  ## Need More Help?
  - "Get help on tools" - Detailed tool information
  - "Get help on parameters" - All parameters explained
  - "Get help on models" - Model selection guide`;
          break;
  
        default:
          helpContent =
            'Unknown help topic. Available topics: overview, tools, models, parameters, examples, quick-start';
      }
  
      return {
        jsonrpc: '2.0',
        id,
        result: {
          content: [
            {
              type: 'text',
              text: helpContent
            }
          ]
        }
      };
    }

• src/utils/validation.ts:107-111 (schema)

  Zod schema definition for validating 'get_help' tool parameters in ToolSchemas.

  getHelp: z.object({
    topic: z
      .enum(['overview', 'tools', 'models', 'parameters', 'examples', 'quick-start'])
      .optional()
  })

• src/enhanced-stdio-server.ts:372-386 (registration)

  The tool registration in getAvailableTools() method, including name, description, and input schema.

  {
    name: 'get_help',
    description: 'Get help and usage information for the Gemini MCP server',
    inputSchema: {
      type: 'object',
      properties: {
        topic: {
          type: 'string',
          description: 'Help topic to get information about',
          enum: ['overview', 'tools', 'models', 'parameters', 'examples', 'quick-start'],
          default: 'overview'
        }
      }
    }
  }

• src/enhanced-stdio-server.ts:980-1156 (helper)

  The getHelpContent helper method provides static help text for different topics used by the get_help handler.

    private getHelpContent(topic: string): string {
      // Extract help content generation to a separate method
      switch (topic) {
        case 'overview':
          return `# Gemini MCP Server Help
  
  Welcome to the Gemini MCP Server v4.1.0! This server provides access to Google's Gemini AI models through Claude Desktop.
  
  ## Available Tools
  1. **generate_text** - Generate text with advanced features
  2. **analyze_image** - Analyze images using vision models
  3. **count_tokens** - Count tokens for cost estimation
  4. **list_models** - List all available models
  5. **embed_text** - Generate text embeddings
  6. **get_help** - Get help on using this server
  
  ## Quick Start
  - "Use Gemini to explain [topic]"
  - "Analyze this image with Gemini"
  - "List all Gemini models"
  - "Get help on parameters"
  
  ## Key Features
  - Latest Gemini 2.5 models with thinking capabilities
  - JSON mode for structured output
  - Google Search grounding for current information
  - System instructions for behavior control
  - Conversation memory for context
  - Safety settings customization
  
  Use "get help on tools" for detailed tool information.`;
  
        case 'tools':
          return `# Available Tools
  
  ## 1. generate_text
  Generate text using Gemini models with advanced features.
  
  **Parameters:**
  - prompt (required): Your text prompt
  - model: Choose from gemini-2.5-pro, gemini-2.5-flash, etc.
  - temperature: 0-2 (default 0.7)
  - maxTokens: Max output tokens (default 2048)
  - systemInstruction: Guide model behavior
  - jsonMode: Enable JSON output
  - grounding: Enable Google Search
  - conversationId: Maintain conversation context
  
  **Example:** "Use Gemini 2.5 Pro to explain quantum computing"
  
  ## 2. analyze_image
  Analyze images using vision-capable models.
  
  **Parameters:**
  - prompt (required): Question about the image
  - imageUrl OR imageBase64 (required): Image source
  - model: Vision-capable model (default gemini-2.5-flash)
  
  **Example:** "Analyze this architecture diagram"
  
  ## 3. count_tokens
  Count tokens for text with a specific model.
  
  **Parameters:**
  - text (required): Text to count
  - model: Model for counting (default gemini-2.5-flash)
  
  **Example:** "Count tokens for this paragraph"
  
  ## 4. list_models
  List available models with optional filtering.
  
  **Parameters:**
  - filter: all, thinking, vision, grounding, json_mode
  
  **Example:** "List models with thinking capability"
  
  ## 5. embed_text
  Generate embeddings for semantic search.
  
  **Parameters:**
  - text (required): Text to embed
  - model: text-embedding-004 or text-multilingual-embedding-002
  
  **Example:** "Generate embeddings for similarity search"
  
  ## 6. get_help
  Get help on using this server.
  
  **Parameters:**
  - topic: overview, tools, models, parameters, examples, quick-start
  
  **Example:** "Get help on parameters"`;
  
        case 'parameters':
          return `# Parameter Reference
  
  ## generate_text Parameters
  
  **Required:**
  - prompt (string): Your text prompt
  
  **Optional:**
  - model (string): Model to use (default: gemini-2.5-flash)
  - systemInstruction (string): System prompt for behavior
  - temperature (0-2): Creativity level (default: 0.7)
  - maxTokens (number): Max output tokens (default: 2048)
  - topK (number): Top-k sampling (default: 40)
  - topP (number): Nucleus sampling (default: 0.95)
  - jsonMode (boolean): Enable JSON output
  - jsonSchema (object): JSON schema for validation
  - grounding (boolean): Enable Google Search
  - conversationId (string): Conversation identifier
  - safetySettings (array): Content filtering settings
  
  ## Temperature Guide
  - 0.1-0.3: Precise, factual
  - 0.5-0.8: Balanced (default 0.7)
  - 1.0-1.5: Creative
  - 1.5-2.0: Very creative
  
  ## JSON Mode Example
  Enable jsonMode and provide jsonSchema:
  {
    "type": "object",
    "properties": {
      "sentiment": {"type": "string"},
      "score": {"type": "number"}
    }
  }
  
  ## Safety Settings
  Categories: HARASSMENT, HATE_SPEECH, SEXUALLY_EXPLICIT, DANGEROUS_CONTENT
  Thresholds: BLOCK_NONE, BLOCK_ONLY_HIGH, BLOCK_MEDIUM_AND_ABOVE, BLOCK_LOW_AND_ABOVE`;
  
        case 'examples':
          return `# Usage Examples
  
  ## Basic Text Generation
  "Use Gemini to explain machine learning"
  
  ## With Specific Model
  "Use Gemini 2.5 Pro to write a Python sorting function"
  
  ## With Temperature
  "Use Gemini with temperature 1.5 to write a creative story"
  
  ## JSON Mode
  "Use Gemini in JSON mode to analyze sentiment and return {sentiment, confidence, keywords}"
  
  ## With Grounding
  "Use Gemini with grounding to research latest AI developments"
  
  ## System Instructions
  "Use Gemini as a Python tutor to explain decorators"
  
  ## Conversation Context
  "Start conversation 'chat-001' about web development"
  "Continue chat-001 and ask about React hooks"
  
  ## Image Analysis
  "Analyze this screenshot and describe the UI elements"
  
  ## Token Counting
  "Count tokens for this document using gemini-2.5-pro"
  
  ## Complex Example
  "Use Gemini 2.5 Pro to review this code with:
  - System instruction: 'You are a security expert'
  - Temperature: 0.3
  - JSON mode with schema for findings
  - Grounding for latest security practices"`;
  
        default:
          return 'Unknown help topic.';
      }
    }