AIM MCP

🚀 AIM Guard MCP

A Model Context Protocol (MCP) server that offers AI - powered security analysis and safety instruction tools. It safeguards AI agents by providing security guidelines, content analysis, and cautionary instructions during interactions with various MCPs and external services.

🛡️ AIM MCP Server :: Guard and Protect your MCPs & AI Agents

🚀 Quick Start

AIM Guard MCP is a powerful MCP server that provides security and protection for AI agents. You can quickly get started by following the installation and usage steps below.

✨ Features

• 🛡️ AI Safety Guard: Before MCP interactions, it offers contextual security instructions and precautions for AI Agents.
• 🔍 Text Guard Analysis: Utilizes the AIM Intelligence API to analyze text content for harmful or inappropriate content.
• 🔒 Security Prompt Enhancement: Adds security instructions to user prompts for safer AI interactions.
• ⚡ Fast & Lightweight: Built with TypeScript and Zod validation.
• 🔧 Easy Integration: Compatible with any MCP - compatible AI assistant.
• 🔗 API Integration: Connects to the AIM Intelligence API for advanced content analysis.

📦 Installation

NPX (Recommended)

npx aim-guard-mcp

Global Installation

npm install -g aim-guard-mcp
aim-guard-mcp

Local Installation

npm install aim-guard-mcp

💻 Usage Examples

As MCP Server

Add to your MCP client configuration:

{
  "servers": {
    "aim-guard": {
      "type": "stdio",
      "command": "npx",
      "args": ["aim-guard-mcp"]
    }
  }
}

Testing the Tools

Test AI Safety Guard

# Get safety instructions for database operations
{
  "name": "ai-safety-guard",
  "arguments": {
    "mcp_type": "database",
    "operation_type": "query",
    "sensitivity_level": "confidential"
  }
}

Test Text Guard

# This will analyze the text for harmful content
{
  "name": "aim-text-guard",
  "arguments": {
    "text": "This is a sample text to analyze for safety."
  }
}

Test Security Prompt Enhancement

# Enhance a user prompt with security instructions
{
  "name": "aim-security-prompt-tool",
  "arguments": {
    "user_prompt": "Please help me with this task",
    "security_level": "strict"
  }
}

Available Tools

1. ai-safety-guard

Provides contextual security instructions and precautions for AI Agents before they interact with other MCPs.

{
  "name": "ai-safety-guard",
  "arguments": {
    "mcp_type": "email|slack|database|file|web|general", // Type of MCP being called
    "operation_type": "read|write|execute|delete|send|query", // Operation being performed
    "sensitivity_level": "public|internal|confidential|restricted" // Data sensitivity level
  }
}

Features:

• Context - aware security guidelines based on MCP type
• Operation - specific warnings and precautions
• Data sensitivity - level protocols and restrictions
• Comprehensive checklists for safe MCP interactions
• Red flag detection and abort recommendations

2. aim-text-guard

Analyze text content for harmful or inappropriate content using the AIM Intelligence API.

{
  "name": "aim-text-guard",
  "arguments": {
    "text": "Text content to analyze for harmful content"
  }
}

Features:

• Real - time content analysis
• Harmful content detection
• Detailed analysis results in JSON format
• Error handling with informative messages
• Timestamp tracking for analysis requests

3. aim-security-prompt-tool

Enhance user prompts with security instructions for safer AI interactions.

{
  "name": "aim-security-prompt-tool",
  "arguments": {
    "user_prompt": "Original user prompt to enhance",
    "security_level": "basic|standard|strict" // Optional, defaults to 'standard'
  }
}

Features:

• Multi - level security enhancement (basic, standard, strict)
• Comprehensive threat analysis instructions
• Social engineering protection guidelines
• Security policy compliance checks
• Sanitization and validation requirements

🔧 Technical Details

🛡️ AI Agent Protection

• MCP Interaction Safety: Contextual guidelines for different MCP types
• Operation Validation: Specific precautions for read/write/execute operations
• Data Sensitivity Handling: Protocols based on data classification levels

🔍 Content Analysis

• Real - time Threat Detection: Analyze content for harmful patterns
• API - powered Analysis: Advanced AI - driven content safety assessment
• Comprehensive Reporting: Detailed security analysis results

🔒 Prompt Security

• Security - Enhanced Prompts: Add protective instructions to user prompts
• Configurable Security Levels: Basic to strict security protocols
• Threat Prevention: Proactive security measures in AI interactions

🚧 Development

# Clone the repository
git clone https://github.com/AIM-Intelligence/AIM-MCP.git
cd AIM-MCP

# Install dependencies
pnpm install

# Build the project
pnpm run build

# Run in development mode
pnpm run dev

# Run tests
pnpm test

🚀 Deployment

This project uses an automated CI/CD pipeline for seamless deployment to NPM.

Automatic Deployment

When you push to the main branch, GitHub Actions will automatically:

1. Build and Test: Compile TypeScript and run tests
2. Version Check: Compare the current version with the published version
3. Publish to NPM: Automatically publish if the version has changed
4. Create Release: Generate a GitHub release with the version tag

Manual Version Management

# Bump patch version (1.0.0 -> 1.0.1)
pnpm run release:patch

# Bump minor version (1.0.0 -> 1.1.0)
pnpm run release:minor

# Bump major version (1.0.0 -> 2.0.0)
pnpm run release:major

Setting up NPM Token

To enable automatic deployment, add your NPM token to GitHub Secrets:

1. Go to npmjs.com and create an automation token
2. In your GitHub repository, go to Settings > Secrets and variables > Actions
3. Add a new secret named NPM_TOKEN with your NPM token value

Deployment Workflow

graph LR
    A[Push to main] --> B[GitHub Actions]
    B --> C[Build & Test]
    C --> D[Version Check]
    D --> E{Version Changed?}
    E -->|Yes| F[Publish to NPM]
    E -->|No| G[Skip Deployment]
    F --> H[Create GitHub Release]
    F --> I[Create Git Tag]

🤝 Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

📄 License

This project is licensed under the ISC License - see the LICENSE file for details.

🛠️ Support

• 📧 Email: support@aim-intelligence.com
• 🐛 Issues: GitHub Issues
• 📖 Documentation: GitHub Wiki

Made with ❤️ by AIM Intelligence