What can you do with this server?

The AIM-Guard-MCP server provides AI-powered security tools for protecting AI agents during interactions with MCPs and external services. * AI Safety Guard: Provides contextual security instructions and precautions based on MCP type, operation, and data sensitivity levels. * Text Guard Analysis: Analyzes text content for harmful or inappropriate material using the AIM Intelligence API, delivering real-time safety assessments. * Security Prompt Enhancement: Enhances user prompts with security instructions at configurable levels (basic, standard, strict) to proactively prevent threats. * Integration: Works seamlessly with MCP-compatible AI assistants and connects to AIM Intelligence API for advanced analysis. * Customization: Supports customizable security levels and detailed reporting for secure AI interactions.

Which integrations are available for this server?

Mentioned in the context of repository management, GitHub releases, and as part of the development workflow Used for automated CI/CD pipeline to build, test, and publish the MCP to NPM Integrated for deployment workflow visualization in documentation Integration for package deployment and publishing through NPM's registry Used for package management in development workflow Provides security guidelines and precautions for AI agents when interacting with Slack, ensuring safe message operations with appropriate sensitivity-level handling Used as the implementation language for the MCP server Integrated for validation of inputs and data structures

How do I use AIM-Guard-MCP?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@AIM-Guard-MCP analyze this text for harmful content" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

AIM-Guard-MCP

by AIM-Intelligence

Overview Schema Related Servers Score Discussions

TypeScript

Remote

AIM Guard MCP

Trust Score

NPM Version Smithery Server

🛡️ 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

Related MCP server: mcp-safeguard

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 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 🆕

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_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

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

Available Tools

6 tools

aim-security-prompt-toolC

Security Prompt Enhancement Tool

ParametersJSON Schema

Name	Required	Description	Default
`user_prompt`	Yes	The original user prompt to enhance with security instructions
`security_level`	No	Security enhancement level	standard

TDQS

C2.2/5.0

Behavior1/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description bears full burden. It only says 'Security Prompt Enhancement Tool', without disclosing any behavioral traits such as whether it modifies the prompt, returns a new string, or has side effects. This is insufficient for an agent to understand the tool's actions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single short phrase, but it is under-specified rather than concise. It lacks essential information to be helpful. Every word should earn its place; here, the phrase barely adds value over the tool name itself.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no output schema and no annotations, the description fails to explain what the tool returns or its behavior. With sibling tools like 'prompt-injection-detector', more context is needed to distinguish usage. The description is incomplete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so schema already explains the two parameters. The description adds no additional meaning beyond the parameter names and defaults. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Security Prompt Enhancement Tool' is a vague noun phrase. It indicates the tool enhances prompts with security but lacks a clear verb and specific resource. It does not differentiate from sibling tools like prompt-injection-detector, which also deals with prompts.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives. The description does not mention prerequisites, exclusions, or context where this tool is appropriate. Sibling tools exist, but no comparative information is provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

aim-text-guardD

AIM-Intelligence Text Guard Tool

ParametersJSON Schema

Name	Required	Description	Default
`text`	Yes	Text to analyze for harmful content

TDQS

D1.6/5.0

Behavior1/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, and the description does not disclose any behavioral traits beyond analyzing text. It fails to mention whether the tool modifies data, requires authentication, or has side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is only 5 words, which is under-specified rather than concise. It provides no useful information and does not front-load key details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema and no annotations, the description is completely inadequate. It does not explain what the tool returns, error conditions, or how to interpret results, making it unusable for an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with one parameter 'text' described as 'Text to analyze for harmful content'. The description adds no additional meaning beyond the schema, so baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose1/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description is 'AIM-Intelligence Text Guard Tool', which is a tautology of the tool name. It does not specify what action the tool performs or what resource it acts on, making it impossible to understand the tool's purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus sibling tools like 'prompt-injection-detector' or 'ai-safety-guard'. The context of analyzing harmful text is implied by the input schema but not explicitly stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

ai-safety-guardD

AI Safety Guard - MCP Caution Instructions for AI Agents

ParametersJSON Schema

Name	Required	Description	Default
`mcp_type`	No	Type of MCP the AI Agent is about to call	general
`operation_type`	No	Type of operation being requested	read
`sensitivity_level`	No	Sensitivity level of the data/operation	internal

TDQS

D1.9/5.0

Behavior1/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description provides no behavioral details (e.g., whether it blocks actions, returns warnings, or modifies behavior). With no annotations, the agent has no insight into side effects or safety implications.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely short (single sentence) but fails to convey essential information. It is under-specified rather than concise; a well-structured description would prioritize key details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given three parameters with enums and no output schema, the description is critically incomplete. It doesn't clarify the tool's output, side effects, or how it integrates with other guard tools. The agent cannot determine correct usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already explains parameters (mcp_type, operation_type, sensitivity_level) with enums. The description adds no additional value beyond what's in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'AI Safety Guard - MCP Caution Instructions for AI Agents' is ambiguous. It does not explicitly state the tool's function (e.g., 'checks safety before calling an MCP' or 'provides safety guidelines'). The purpose is implied but not clearly conveyed.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when or why to use this tool versus siblings like 'prompt-injection-detector' or 'credential-scanner'. The description lacks context for appropriate invocation, forcing the agent to guess.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

credential-scannerB

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

ParametersJSON Schema

Name	Required	Description	Default
`text`	Yes	Text to scan for credentials
`mask_findings`	No	Mask detected credentials in output

TDQS

B3.4/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must disclose behavioral traits. It only states the scanning function, omitting key details such as whether the tool modifies the input, what it returns, or any performance implications. The 'mask_findings' parameter hints at output masking but is not explained.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence that efficiently conveys the core functionality. No extraneous information is present.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simplicity of the tool, the description lacks crucial details such as output format, behavior when credentials are found vs. not, and how masking works. Without an output schema, these omissions hinder complete understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Both parameters are well-described in the input schema (100% coverage). The description adds no further semantic value beyond the schema definitions, meeting the baseline expectation but not exceeding it.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool scans text for exposed credentials, listing specific types (API keys, passwords, tokens, SSH keys). This distinct purpose is easily differentiated from sibling tools like 'prompt-injection-detector' or 'url-security-validator'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies use for credential detection but offers no explicit guidance on when to use or not use this tool versus alternatives. No context on potential false positives or limitations is provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

prompt-injection-detectorC

Detect prompt injection attempts based on OWASP LLM01:2025 patterns

ParametersJSON Schema

Name	Required	Description	Default
`text`	Yes	Text to analyze for prompt injection patterns
`sensitivity`	No	Detection sensitivity level	medium

TDQS

C2.9/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. It does not disclose return format, whether it's a binary or score, or any side effects. Lacks behavioral details beyond detection itself.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single sentence that efficiently conveys the core purpose. Could include more detail without losing conciseness, but current length is appropriate.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description should hint at return values or detection output. It does not, leaving a gap in understanding tool behavior. Context signals indicate only 2 simple parameters, but output is undocumented.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema covers 100% of parameters with descriptions. The description adds no additional meaning beyond the schema, achieving the baseline for high coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool detects prompt injection attempts using OWASP LLM01:2025 patterns, providing a specific verb and resource. It implicitly differentiates from sibling tools like 'aim-security-prompt-tool' by focusing on OWASP patterns, but does not explicitly contrast them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives (e.g., aim-text-guard, credential-scanner). Missing context about appropriate scenarios or limitations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

url-security-validatorA

Validate URL safety (phishing, malware, HTTPS enforcement)

ParametersJSON Schema

Name	Required	Description	Default
`url`	Yes	URL to validate for security
`strict_mode`	No	Enable strict security checks

TDQS

A3.8/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations exist, so the description carries full burden. It names specific security checks (phishing, malware, HTTPS enforcement) but does not disclose whether the tool is read-only, authentication needs, or any side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence that conveys the essential purpose without any redundant or extraneous information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite a simple interface, the lack of output schema means the description should hint at the return format (e.g., boolean, object). It fails to do so, leaving the agent uncertain about what the tool returns.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents both parameters. The description does not add meaning beyond what the schema provides, meeting the baseline of 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states the tool validates URL safety for phishing, malware, and HTTPS enforcement, clearly identifying the verb and resource. It distinguishes from sibling safety tools like prompt-injection-detector and credential-scanner.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for URL security validation but does not provide explicit when-to-use or when-not-to-use guidance. The context is clear, but no exclusions or alternatives are mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

3 tool updatesv1.3.1May 10, 2026
- Addedcredential-scanner
- Addedprompt-injection-detector
- Addedurl-security-validator
3 tool updatesv1.0.0Aug 15, 2025
- First observedai-safety-guard
- First observedaim-security-prompt-tool
- First observedaim-text-guard

Install Server

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TDQS

C2.9/5.0

Disambiguation5/5

Each tool targets a specific security concern: prompt enhancement, text guard, safety instructions, credential scanning, injection detection, and URL validation. There is no overlap in their purposes.

Naming Consistency4/5

All tool names use snake_case and are noun phrases, but some have an 'aim-' prefix while others do not (e.g., 'credential-scanner' vs. 'aim-security-prompt-tool'). This minor inconsistency prevents a perfect score.

Tool Count5/5

Six tools is an appropriate number for a security-focused server. Each tool addresses a distinct aspect of AI safety without redundancy or unnecessary complexity.

Completeness4/5

The tools cover major security areas: prompt injection, credential leaks, URL safety, and general AI safety. Missing a tool for data leakage beyond credentials, but overall coverage is solid for the domain.

Maintenance

ActivityInactive

ResponsivenessSyncing

Resources

Need Help?

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AIM Guard MCP

Features

🔧 Tools (6 total)

📚 Resources (9 total)

💬 Prompts (2 total)

🎯 General

Installation

Installing via Smithery

NPX (Recommended)

Global Installation

Local Installation

Usage

As MCP Server

Testing the Tools

Test AI Safety Guard

Test Text Guard

Test Security Prompt Enhancement

Available Tools

1. ai-safety-guard

2. aim-text-guard

3. aim-security-prompt-tool

4. prompt-injection-detector 🆕

5. credential-scanner 🆕

6. url-security-validator 🆕

Available Resources 🆕

Security Checklists

Security Policies

Available Prompts 🆕

1. security-review

2. threat-analysis

Security Features

🛡️ AI Agent Protection

🔍 Content Analysis

🌐 URL Security

📚 Policy & Compliance

🔒 Workflow Orchestration

Development

Deployment

Automatic Deployment

Manual Version Management

Setting up NPM Token

Deployment Workflow

Contributing

License

Documentation

Support

Available Tools

Tool Schema Changelog

Maintenance

Resources

Looking for Admin?

Related MCP Connectors

Related MCP Servers

Appeared in Searches

Latest Blog Posts

MCP directory API

1. `ai-safety-guard`

2. `aim-text-guard`

3. `aim-security-prompt-tool`

4. `prompt-injection-detector` 🆕

5. `credential-scanner` 🆕

6. `url-security-validator` 🆕

1. `security-review`

2. `threat-analysis`