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
🔧 Tools (6 total)
- 🛡️ AI Safety Guard: Contextual security instructions for MCP interactions
- 🔍 Text Guard Analysis: Harmful content detection using AIM Intelligence API
- 🔒 Security Prompt Enhancement: Add security layers to user prompts
- 🚨 Prompt Injection Detector: OWASP LLM01:2025 compliant injection detection
- 🔐 Credential Scanner: Scan for exposed API keys, passwords, tokens, and secrets
- 🌐 URL Security Validator: Validate URLs for phishing, malware, and HTTPS enforcement
📚 Resources (9 total)
- 📋 Security Checklists: MCP-specific security checklists (database, email, slack, file, web, general)
- 📖 Security Policies: Comprehensive policies (data classification, access control, incident response)
💬 Prompts (2 total)
- 🔍 Security Review: Multi-step security review workflow
- ⚠️ Threat Analysis: STRIDE-based threat modeling and risk assessment
🎯 General
- ⚡ 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 analysis
- 📚 Comprehensive Documentation: Detailed guide for Tools, Resources, and Prompts
Installation
Installing via Smithery
To install aim-mcp for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @AIM-Intelligence/aim-mcp --client claude
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",
"operation_type": "read|write|execute|delete|send|query",
"sensitivity_level": "public|internal|confidential|restricted"
}
}
Features: Context-aware guidelines, operation-specific warnings, red flag detection
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"
}
}
Features: Real-time analysis, harmful content detection, detailed JSON results
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",
"security_level": "basic|standard|strict"
}
}
Features: Multi-level enhancement, threat analysis, social engineering protection
4. prompt-injection-detector 🆕
Detect prompt injection attempts based on OWASP LLM01:2025 patterns.
{
"name": "prompt-injection-detector",
"arguments": {
"text": "Text to analyze for injection patterns",
"sensitivity": "low|medium|high"
}
}
Features:
- 15+ injection pattern detection (instruction override, role manipulation, jailbreak attempts)
- Risk scoring (0-100) with severity assessment
- OWASP LLM01:2025 compliant
- Configurable sensitivity levels
- Detailed threat reporting
5. credential-scanner 🆕
Scan text for exposed credentials including API keys, passwords, tokens, and SSH keys.
{
"name": "credential-scanner",
"arguments": {
"text": "Text to scan for credentials",
"mask_findings": true
}
}
Features:
- 50+ credential patterns (AWS, GitHub, Google, OpenAI, Stripe, JWT, SSH keys)
- Automatic credential masking
- Risk level assessment
- Platform-specific detection (AWS, GitHub, Slack, databases)
- Actionable security recommendations
6. url-security-validator 🆕
Validate URL safety for phishing, malware, and security issues.
{
"name": "url-security-validator",
"arguments": {
"url": "URL to validate",
"strict_mode": false
}
}
Features:
- 10+ security checks (protocol, TLD, IP address, homograph attacks)
- Phishing domain detection
- URL shortener identification
- Suspicious parameter detection
- HTTPS enforcement validation
Available Resources 🆕
Resources provide read-only security documentation and policies accessible via URI schemes.
Security Checklists
Access via security-checklist://[type]
security-checklist://database- Database operations checklistsecurity-checklist://email- Email operations checklistsecurity-checklist://slack- Chat/messaging operations checklistsecurity-checklist://file- File operations checklistsecurity-checklist://web- Web request checklistsecurity-checklist://general- General MCP operations checklist
Each checklist includes:
- Pre-operation checks
- During-operation guidelines
- Post-operation verification
- Red flags to abort operations
Security Policies
Access via security-policy://[type]
security-policy://data-classification- Data classification levels and handling requirementssecurity-policy://access-control- Access control principles and authentication requirementssecurity-policy://incident-response- Incident response procedures and severity levels
Available Prompts 🆕
Prompts provide reusable workflow templates for complex security operations.
1. security-review
Comprehensive security review workflow for code, data, or configuration.
{
"name": "security-review",
"arguments": {
"target_type": "code|data|configuration",
"context": "Additional context (optional)"
}
}
Workflow:
- Credential scanning
- Prompt injection detection (if applicable)
- Security checklist consultation
- Policy compliance review
- Threat analysis
- Risk assessment and recommendations
- Summary table - Visual overview of all findings by severity
Summary Output Example:
📊 요약
| 심각도 | 개수 | 파일/위치 |
|-------------|-----|------------------------|
| 🔴 CRITICAL | 1 | resources/handler.ts |
| 🟠 HIGH | 2 | textGuard.ts |
| 🟡 MEDIUM | 3 | prompts/handler.ts |
| 🟢 LOW | 5 | credentialScanner.ts |
2. threat-analysis
Analyze potential security threats using STRIDE methodology.
{
"name": "threat-analysis",
"arguments": {
"scenario": "Security scenario to analyze",
"sensitivity_level": "public|internal|confidential|restricted"
}
}
Framework:
- Asset identification
- STRIDE threat modeling (Spoofing, Tampering, Repudiation, Information Disclosure, DoS, Elevation of Privilege)
- Risk assessment (likelihood × impact)
- Attack vector analysis
- Control gap identification
- Mitigation strategies
- Compliance considerations
- Incident response planning
- Summary table - Visual overview of all threats by severity
Summary Output Example:
📊 요약
| 심각도 | 개수 | 위협 유형 |
|-------------|-----|---------------------------------|
| 🔴 CRITICAL | 2 | Information Disclosure, Spoofing |
| 🟠 HIGH | 1 | Elevation of Privilege |
| 🟡 MEDIUM | 3 | Tampering, DoS |
| 🟢 LOW | 1 | Repudiation |
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
- Prompt Injection Detection: OWASP LLM01:2025 compliant pattern matching
- Credential Exposure Prevention: Scan for 50+ types of exposed secrets
- API-powered Analysis: Advanced AI-driven content safety assessment
🌐 URL Security
- Phishing Detection: Identify suspicious domains and homograph attacks
- HTTPS Enforcement: Validate secure protocol usage
- Malicious URL Blocking: Check against known threat indicators
📚 Policy & Compliance
- Security Checklists: Pre-built checklists for all MCP types
- Data Classification: Clear policies for handling sensitive data
- Access Control: Guidelines for authentication and authorization
- Incident Response: Structured procedures for security incidents
🔒 Workflow Orchestration
- Security Review Prompts: Multi-step review workflows
- Threat Analysis: STRIDE-based threat modeling
- Automated Audits: Combine multiple tools for comprehensive checks
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:
- Build and Test: Compile TypeScript and run tests
- Version Check: Compare current version with published version
- Publish to NPM: Automatically publish if version has changed
- 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:
- Go to npmjs.com and create an automation token
- In your GitHub repository, go to Settings > Secrets and variables > Actions
- Add a new secret named
NPM_TOKENwith 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
- Fork the repository
- Create your feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add some amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
License
This project is licensed under the ISC License - see the LICENSE file for details.
Documentation
- 📚 MCP Components Guide: Comprehensive guide to Tools, Resources, and Prompts
- 📖 GitHub Wiki: Additional documentation and examples
- 🔍 MCP Specification: Official Model Context Protocol documentation
Support
- 📧 Email: support@aim-intelligence.com
- 🐛 Issues: GitHub Issues
- 💬 Discussions: GitHub Discussions
Made with ❤️ by AIM Intelligence