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    Mcp Ai Bridge

    4 stars
    JavaScript
    Updated Oct 7, 2025

    Table of Contents

    • Features
    • Installation
    • Configuration in Claude Code
    • Method 1: Using Claude Code CLI (Recommended)
    • Method 2: Manual Configuration
    • Method 3: Import from Claude Desktop
    • Available Tools
    • 1. ask_openai
    • 2. ask_gemini
    • 3. server_info
    • Usage Examples
    • Debugging MCP Server
    • Testing
    • Test Coverage
    • Troubleshooting
    • Common Issues
    • Claude Code Specific Troubleshooting
    • Security Features
    • Enhanced Security Protection
    • Security Levels
    • Granular Security Configuration
    • Best Practices
    • Rate Limiting

    Table of Contents

    • Features
    • Installation
    • Configuration in Claude Code
    • Method 1: Using Claude Code CLI (Recommended)
    • Method 2: Manual Configuration
    • Method 3: Import from Claude Desktop
    • Available Tools
    • 1. ask_openai
    • 2. ask_gemini
    • 3. server_info
    • Usage Examples
    • Debugging MCP Server
    • Testing
    • Test Coverage
    • Troubleshooting
    • Common Issues
    • Claude Code Specific Troubleshooting
    • Security Features
    • Enhanced Security Protection
    • Security Levels
    • Granular Security Configuration
    • Best Practices
    • Rate Limiting

    Documentation

    MCP AI Bridge

    A secure Model Context Protocol (MCP) server that bridges Claude Code with OpenAI and Google Gemini APIs.

    Features

    • OpenAI Integration: Access GPT-4o, GPT-4o Mini, GPT-4 Turbo, GPT-4, and reasoning models (o1, o1-mini, o1-pro, o3-mini)
    • Gemini Integration: Access Gemini 1.5 Pro, Gemini 1.5 Flash, and vision models with latest capabilities
    • Security Features:
    • Enhanced Input Validation: Multi-layer validation with sanitization
    • Content Filtering: Blocks explicit, harmful, and illegal content
    • Prompt Injection Detection: Identifies and blocks manipulation attempts
    • Rate Limiting: Prevents API abuse with configurable limits
    • Secure Error Handling: No sensitive information exposure
    • API Key Validation: Format validation for API keys
    • Configurable Security Levels: Basic, Moderate, and Strict modes
    • Robust Error Handling: Specific error types with detailed messages
    • Structured Logging: Winston-based logging with configurable levels
    • Flexible Configuration: Control temperature and model selection for each request

    Installation

    1. Clone or copy the mcp-ai-bridge directory to your preferred location

    2. Install dependencies:

    bash
    cd mcp-ai-bridge
    npm install

    3. Configure your API keys using ONE of these methods:

    Option A: Use global .env file in your home directory (Recommended)

    • Create or edit ~/.env file
    • Add your API keys:
    code
    OPENAI_API_KEY=your_openai_api_key_here
         GOOGLE_AI_API_KEY=your_google_ai_api_key_here

    Option B: Use local .env file

    • Create a .env file in the mcp-ai-bridge directory:
    bash
    cp .env.example .env
    • Add your API keys to this local .env file

    Option C: Use environment variables in Claude Code config

    • Configure directly in the Claude Code settings (see Configuration section)

    The server will check for environment variables in this order:

    1. ~/.env (your home directory)

    2. ./.env (local to mcp-ai-bridge directory)

    3. System environment variables

    4. Optional Configuration Variables:

    code
    # Logging level (error, warn, info, debug)
       LOG_LEVEL=info
       
       # Server identification
       MCP_SERVER_NAME=AI Bridge
       MCP_SERVER_VERSION=1.0.0
       
       # Security Configuration
       SECURITY_LEVEL=moderate              # disabled, basic, moderate, strict
       
       # Content Filtering (granular controls)
       BLOCK_EXPLICIT_CONTENT=true         # Master content filter toggle
       BLOCK_VIOLENCE=true                  # Block violent content
       BLOCK_ILLEGAL_ACTIVITIES=true       # Block illegal activity requests
       BLOCK_ADULT_CONTENT=true             # Block adult/sexual content
       
       # Injection Detection (granular controls)
       DETECT_PROMPT_INJECTION=true        # Master injection detection toggle
       DETECT_SYSTEM_PROMPTS=true           # Detect system role injections
       DETECT_INSTRUCTION_OVERRIDE=true     # Detect "ignore instructions" attempts
       
       # Input Sanitization (granular controls)
       SANITIZE_INPUT=true                  # Master sanitization toggle
       REMOVE_SCRIPTS=true                  # Remove script tags and JS
       LIMIT_REPEATED_CHARS=true            # Limit DoS via repeated characters
       
       # Performance & Flexibility
       ENABLE_PATTERN_CACHING=true          # Cache compiled patterns for speed
       MAX_PROMPT_LENGTH_FOR_DEEP_SCAN=1000 # Skip deep scanning for long prompts
       ALLOW_EDUCATIONAL_CONTENT=false      # Whitelist educational content
       WHITELIST_PATTERNS=                  # Comma-separated regex patterns to allow

    Configuration in Claude Code

    Method 1: Using Claude Code CLI (Recommended)

    Use the interactive MCP setup wizard:

    bash
    claude mcp add

    Or add the server configuration directly:

    bash
    claude mcp add-json ai-bridge '{"command": "node", "args": ["/path/to/mcp-ai-bridge/src/index.js"]}'

    Method 2: Manual Configuration

    Add the following to your Claude Code MCP settings. The configuration file location depends on your environment:

    • Claude Code CLI: Uses settings.json in the configuration directory (typically ~/.claude/ or $CLAUDE_CONFIG_DIR)
    • Claude Desktop: Uses ~/.claude/claude_desktop_config.json

    For Claude Desktop compatibility:

    json
    {
      "mcpServers": {
        "ai-bridge": {
          "command": "node",
          "args": ["/path/to/mcp-ai-bridge/src/index.js"],
          "env": {
            "OPENAI_API_KEY": "your_openai_api_key",
            "GOOGLE_AI_API_KEY": "your_google_ai_api_key"
          }
        }
      }
    }

    Alternatively, if you have the .env file configured, you can omit the env section:

    json
    {
      "mcpServers": {
        "ai-bridge": {
          "command": "node",
          "args": ["/path/to/mcp-ai-bridge/src/index.js"]
        }
      }
    }

    Method 3: Import from Claude Desktop

    If you already have this configured in Claude Desktop, you can import the configuration:

    bash
    claude mcp add-from-claude-desktop

    Available Tools

    1. ask_openai

    Query OpenAI models with full validation and security features.

    Parameters:

    • prompt (required): The question or prompt to send (max 10,000 characters)
    • model (optional): Choose from 'gpt-4o', 'gpt-4o-mini', 'gpt-4-turbo', 'gpt-4', 'o1', 'o1-mini', 'o1-pro', 'o3-mini', 'chatgpt-4o-latest', and other available models (default: 'gpt-4o-mini')
    • temperature (optional): Control randomness (0-2, default: 0.7)

    Security Features:

    • Input validation for prompt length and type
    • Temperature range validation
    • Model validation
    • Rate limiting (100 requests per minute by default)

    2. ask_gemini

    Query Google Gemini models with full validation and security features.

    Parameters:

    • prompt (required): The question or prompt to send (max 10,000 characters)
    • model (optional): Choose from 'gemini-1.5-pro-latest', 'gemini-1.5-pro-002', 'gemini-1.5-pro', 'gemini-1.5-flash-latest', 'gemini-1.5-flash', 'gemini-1.5-flash-002', 'gemini-1.5-flash-8b', 'gemini-1.0-pro-vision-latest', 'gemini-pro-vision' (default: 'gemini-1.5-flash-latest')
    • temperature (optional): Control randomness (0-1, default: 0.7)

    Security Features:

    • Input validation for prompt length and type
    • Temperature range validation
    • Model validation
    • Rate limiting (100 requests per minute by default)

    3. server_info

    Get comprehensive server status and configuration information.

    Returns:

    • Server name and version
    • Available models for each service
    • Security settings (rate limits, validation status)
    • Configuration status for each API

    Usage Examples

    In Claude Code, you can use these tools like:

    code
    mcp__ai-bridge__ask_openai
      prompt: "Explain the concept of recursion in programming"
      model: "gpt-4o"
      temperature: 0.5
    
    mcp__ai-bridge__ask_gemini
      prompt: "What are the key differences between Python and JavaScript?"
      model: "gemini-1.5-flash-latest"
    
    mcp__ai-bridge__server_info

    Debugging MCP Server

    If you encounter issues with the MCP server, you can use Claude Code's debugging features:

    bash
    # Enable MCP debug mode for detailed error information
    claude --mcp-debug
    
    # Check MCP server status and tools
    claude
    # Then use the /mcp slash command to view server details

    Testing

    The project includes comprehensive unit tests and security tests. To run tests:

    bash
    # Run all tests (including security tests)
    npm test
    
    # Run tests in watch mode
    npm run test:watch
    
    # Run tests with coverage report
    npm run test:coverage

    Test Coverage

    • Unit tests for all server functionality
    • Security tests for input validation and rate limiting
    • Integration tests for API interactions
    • Error handling tests
    • Mock-based testing to avoid real API calls

    Troubleshooting

    Common Issues

    1. "API key not configured" error: Make sure you've added the correct API keys to your .env file or Claude Code config

    2. "Invalid OpenAI API key format" error: OpenAI keys must start with 'sk-'

    3. "Rate limit exceeded" error: Wait for the rate limit window to reset (default: 1 minute)

    4. "Prompt too long" error: Keep prompts under 10,000 characters

    5. Module not found errors: Run npm install in the mcp-ai-bridge directory

    6. Permission errors: Ensure the index.js file has execute permissions

    7. Logging issues: Set LOG_LEVEL environment variable (error, warn, info, debug)

    Claude Code Specific Troubleshooting

    8. MCP server not loading:

    • Use claude --mcp-debug to see detailed error messages
    • Check server configuration with /mcp slash command
    • Verify the server path is correct and accessible
    • Ensure Node.js is installed and in your PATH

    9. Configuration issues:

    • Use claude mcp add for interactive setup
    • Check CLAUDE_CONFIG_DIR environment variable if using custom config location
    • For timeouts, configure MCP_TIMEOUT and MCP_TOOL_TIMEOUT environment variables

    10. Server startup failures:

    • Check if the server process can start independently: node /path/to/mcp-ai-bridge/src/index.js
    • Verify all dependencies are installed
    • Check file permissions on the server directory

    Security Features

    Enhanced Security Protection

    • Multi-Layer Input Validation: Type, length, and content validation
    • Content Filtering: Blocks explicit, violent, illegal, and harmful content
    • Prompt Injection Detection: Identifies and prevents manipulation attempts including:
    • Instruction override attempts ("ignore previous instructions")
    • System role injection ("system: act as...")
    • Template injection ({{system}}, , [INST])
    • Suspicious pattern detection
    • Input Sanitization: Removes control characters, scripts, and malicious patterns
    • Rate Limiting: 100 requests per minute by default to prevent API abuse
    • API Key Validation: Format validation for API keys before use
    • Secure Error Handling: No stack traces or sensitive information in error messages
    • Structured Logging: All operations are logged with appropriate levels

    Security Levels

    • Basic: Minimal filtering, allows most content
    • Moderate (Default): Balanced protection with reasonable restrictions
    • Strict: Maximum protection, blocks borderline content

    Granular Security Configuration

    Security Levels:

    • disabled - No security checks (maximum performance)
    • basic - Essential protection only (good performance)
    • moderate - Balanced protection (default, good balance)
    • strict - Maximum protection (may impact performance)

    Individual Feature Controls:

    bash
    # Master toggles
    SECURITY_LEVEL=moderate
    BLOCK_EXPLICIT_CONTENT=true
    DETECT_PROMPT_INJECTION=true
    SANITIZE_INPUT=true
    
    # Granular content filtering
    BLOCK_VIOLENCE=true                  # "how to kill", violence
    BLOCK_ILLEGAL_ACTIVITIES=true       # "how to hack", illegal acts
    BLOCK_ADULT_CONTENT=true            # Sexual/adult content
    
    # Granular injection detection
    DETECT_SYSTEM_PROMPTS=true           # "system: act as admin"
    DETECT_INSTRUCTION_OVERRIDE=true     # "ignore previous instructions"
    
    # Granular sanitization
    REMOVE_SCRIPTS=true                  # Remove  tags
    LIMIT_REPEATED_CHARS=true           # Prevent character flooding
    
    # Performance optimization
    ENABLE_PATTERN_CACHING=true         # Cache patterns for speed
    MAX_PROMPT_LENGTH_FOR_DEEP_SCAN=1000 # Skip intensive checks on long prompts
    
    # Flexibility options
    ALLOW_EDUCATIONAL_CONTENT=true      # Whitelist "research about", "explain"
    WHITELIST_PATTERNS="educational,academic" # Custom regex patterns

    Performance Considerations:

    • Pattern caching reduces regex compilation overhead
    • Long prompts (>1000 chars) get lighter scanning in basic mode
    • Early termination stops checking after finding issues
    • Granular controls let you disable unneeded checks

    Best Practices

    • Never commit your .env file to version control
    • Keep your API keys secure and rotate them regularly
    • Consider setting usage limits on your API accounts
    • Monitor logs for unusual activity
    • Use the rate limiting feature to control costs
    • Validate the server configuration using the server_info tool

    Rate Limiting

    The server implements sliding window rate limiting:

    • Default: 100 requests per minute
    • Configurable via environment variables
    • Per-session tracking
    • Graceful error messages with reset time information

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