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AIM Guard

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aim-intelligence

AIM MCP Server :: Guard and Protect your MCPs & AI Chatting

Publisheraim-intelligence
Repositoryaim-mcp
LanguageTypeScript
Forks
16
Stars
20
Available tools
6
Transport typestdio
Categories
LicenseISC
Links
  • Connect tools to AI workflows

    AIM Guard exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 6 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    20 stars and 16 forks from the linked repository.

en ko

AIM Guard MCP

Trust Score smithery badge

NPM Version Smithery Server

πŸ›‘οΈ 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

πŸ”§ Tools (6 total)

  • πŸ›‘οΈ AI Safety Guard: Contextual security instructions for MCP interactions
  • πŸ” Text Guard Analysis: Harmful content detection using AIM Intelligence API
  • πŸ”’ Security Prompt Enhancement: Add security layers to user prompts
  • 🚨 Prompt Injection Detector: OWASP LLM01:2025 compliant injection detection
  • πŸ” Credential Scanner: Scan for exposed API keys, passwords, tokens, and secrets
  • 🌐 URL Security Validator: Validate URLs for phishing, malware, and HTTPS enforcement

πŸ“š Resources (9 total)

  • πŸ“‹ Security Checklists: MCP-specific security checklists (database, email, slack, file, web, general)
  • πŸ“– Security Policies: Comprehensive policies (data classification, access control, incident response)

πŸ’¬ Prompts (2 total)

  • πŸ” 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
  • πŸ”§ Easy Integration: Works with any MCP-compatible AI assistant
  • πŸ”— API Integration: Connects to AIM Intelligence API for advanced analysis
  • πŸ“š Comprehensive Documentation: Detailed guide for Tools, Resources, and Prompts

Installation

Installing via Smithery

To install aim-mcp for Claude Desktop automatically via Smithery:

bash
npx -y @smithery/cli install @AIM-Intelligence/aim-mcp --client claude

NPX (Recommended)

bash
npx aim-guard-mcp

Global Installation

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

Local Installation

bash
npm install aim-guard-mcp

Usage

As MCP Server

Add to your MCP client configuration:

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

Testing the Tools

Test AI Safety Guard

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

Test Text Guard

bash
# 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

bash
# 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.

json
{
  "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.

json
{
  "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.

json
{
  "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 πŸ†•

Detect prompt injection attempts based on OWASP LLM01:2025 patterns.

json
{
  "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 πŸ†•

Scan text for exposed credentials including API keys, passwords, tokens, and SSH keys.

json
{
  "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 πŸ†•

Validate URL safety for phishing, malware, and security issues.

json
{
  "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 πŸ†•

Resources provide read-only security documentation and policies accessible via URI schemes.

Security Checklists

Access via security-checklist://[type]

  • security-checklist://database - Database operations checklist
  • security-checklist://email - Email operations checklist
  • security-checklist://slack - Chat/messaging operations checklist
  • security-checklist://file - File operations checklist
  • security-checklist://web - Web request checklist
  • security-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 requirements
  • security-policy://access-control - Access control principles and authentication requirements
  • security-policy://incident-response - Incident response procedures and severity levels

Available Prompts πŸ†•

Prompts provide reusable workflow templates for complex security operations.

1. security-review

Comprehensive security review workflow for code, data, or configuration.

json
{
  "name": "security-review",
  "arguments": {
    "target_type": "code|data|configuration",
    "context": "Additional context (optional)"
  }
}

Workflow:

  1. Credential scanning
  2. Prompt injection detection (if applicable)
  3. Security checklist consultation
  4. Policy compliance review
  5. Threat analysis
  6. Risk assessment and recommendations
  7. Summary table - Visual overview of all findings by severity

Summary Output Example:

πŸ“Š μš”μ•½

| 심각도         | 개수  | 파일/μœ„μΉ˜                  |
|-------------|-----|------------------------|
| πŸ”΄ 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.

json
{
  "name": "threat-analysis",
  "arguments": {
    "scenario": "Security scenario to analyze",
    "sensitivity_level": "public|internal|confidential|restricted"
  }
}

Framework:

  1. Asset identification
  2. STRIDE threat modeling (Spoofing, Tampering, Repudiation, Information Disclosure, DoS, Elevation of Privilege)
  3. Risk assessment (likelihood Γ— impact)
  4. Attack vector analysis
  5. Control gap identification
  6. Mitigation strategies
  7. Compliance considerations
  8. Incident response planning
  9. Summary table - Visual overview of all threats by severity

Summary Output Example:

πŸ“Š μš”μ•½

| 심각도         | 개수  | μœ„ν˜‘ μœ ν˜•                           |
|-------------|-----|---------------------------------|
| πŸ”΄ CRITICAL | 2   | Information Disclosure, Spoofing |
| 🟠 HIGH     | 1   | Elevation of Privilege           |
| 🟑 MEDIUM   | 3   | Tampering, DoS                   |
| 🟒 LOW      | 1   | Repudiation                      |

Security Features

πŸ›‘οΈ 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

πŸ” 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

πŸ“š 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

πŸ”’ Workflow Orchestration

  • Security Review Prompts: Multi-step review workflows
  • Threat Analysis: STRIDE-based threat modeling
  • Automated Audits: Combine multiple tools for comprehensive checks

Development

bash
# 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

bash
# 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

mermaid
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.

Documentation

Support


Made with ❀️ by AIM Intelligence

Installation

TypingMind
Prerequisites:

Node.js 18+

{
  "mcpServers": {
    "aim-guard": {
      "command": "npx",
      "args": [
        "aim-guard-mcp"
      ]
    }
  }
}

Available Tools

  • ai-safety-guard

    AI Safety Guard - MCP Caution Instructions for AI Agents

  • aim-text-guard

    AIM-Intelligence Text Guard Tool

  • aim-security-prompt-tool

    Security Prompt Enhancement Tool

  • prompt-injection-detector

    Detect prompt injection attempts based on OWASP LLM01:2025 patterns

  • credential-scanner

    Scan text for exposed credentials (API keys, passwords, tokens, SSH keys)

  • url-security-validator

    Validate URL safety (phishing, malware, HTTPS enforcement)

Use AIM Guard MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once AIM Guard is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add AIM Guard as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the AIM Guard MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "aim-guard": {
      "command": "npx",
      "args": [
        "-y",
        "aim-guard-mcp"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the AIM Guard MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the AIM Guard MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use AIM Guard to help me with this task?
AIM Guard
Sure. I read it.
Here is what I found using AIM Guard.

Frequently asked questions

What is the AIM Guard MCP server used for?

AIM Guard is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use AIM Guard MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use AIM Guard with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use AIM Guard MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With AIM Guard connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect AIM Guard MCP to TypingMind?

AIM Guard runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does AIM Guard MCP provide in TypingMind?

AIM Guard exposes 6 MCP tools that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use AIM Guard MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If AIM Guard requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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