AIM-MCP

AIM-Intelligence/AIM-MCP

3.3

If you are the rightful owner of AIM-MCP and would like to certify it and/or have it hosted online, please leave a comment on the right or send an email to henry@mcphub.com.

AIM Guard MCP is a server designed to enhance the security and safety of AI agents interacting with various Model Context Protocols (MCPs).

AIM Guard MCP

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

A Model Context Protocol (MCP) server that provides AI-powered security analysis and safety instruction tools. This server helps protect AI agents by providing security guidelines, content analysis, and cautionary instructions when interacting with various MCPs and external services.

Features

  • 🛡️ AI Safety Guard: Provides contextual security instructions and precautions for AI Agents before MCP interactions
  • 🔍 Text Guard Analysis: Analyze text content for harmful or inappropriate content using AIM Intelligence API
  • 🔒 Security Prompt Enhancement: Add security instructions to user prompts for safer AI interactions
  • ⚡ Fast & Lightweight: Built with TypeScript and Zod validation
  • 🔧 Easy Integration: Works with any MCP-compatible AI assistant
  • 🔗 API Integration: Connects to 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

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
  • 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 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

Security Features

🛡️ 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 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 current version with published version
  3. Publish to NPM: Automatically publish if version has changed
  4. Create Release: Generate GitHub release with 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 file for details.

Support

Made with ❤️ by AIM Intelligence