# Python Code Safety Linter MCP for AI Agents AI Agent Connect

> Python Code Safety Linter acts as a security gatekeeper for code generated by your AI client. It uses Abstract Syntax Tree analysis to inspect Python code for dangerous functions, restricted modules, and infinite loop risks without actually running the code. This ensures that any script your agent writes or suggests is safe to execute in your environment.

## Overview
- **Category:** security
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_x1ckNcFBAQnapMBxq8ev6N59e1TC0dLuvgwnqp8a/ai-agent-connect
- **Tags:** ast, security, python, linter, safety

## Description

When you ask an AI to write Python code, you're essentially asking it to write instructions that your computer will follow. If that code includes a command to delete files or access sensitive system data, you're in trouble. This MCP provides a safety net by inspecting the structure of the code before it ever touches your terminal. Instead of just guessing if a script is safe, your agent can now perform a deep structural audit to find hidden risks.

It looks for the bad stuff—like attempts to use restricted system modules or calls to dangerous functions that could compromise your machine. It even catches logic errors like infinite loops that could hang your system. By connecting this to your workflow through the Vinkius catalog, you add a layer of deterministic security to the probabilistic nature of AI. You get to stop worrying about whether a snippet of code is a clever solution or a security liability, because the audit happens every single time.

## Tools

### analyze_code_safety
Performs a full security audit of Python code using AST traversal. It catches dangerous functions and module imports.

### check_module_whitelist
Checks if a specific Python module is allowed in your current security context. It helps enforce strict environment rules.

### summarize_security_report
Converts technical audit data into a clear summary. It makes it easy to understand the risks found in a script.

## Prompt Examples

**Prompt:** 
```
Is this Python code safe to run: 'import os; os.system("ls")'?
```

**Response:** 
```
No, this code is **unsafe**. 

**Risks detected:**
* **Restricted Module:** The code attempts to import `os`.
* **Dangerous Function:** The call to `os.system` is a high-risk operation that allows arbitrary command execution.
```

**Prompt:** 
```
Check if this script has any infinite loop risks: 'while True: print("working")'
```

**Response:** 
```
This script is **unsafe**.

**Risk detected:**
* **Infinite Loop:** The `While` node contains a condition that will never evaluate to false, which will cause the process to run indefinitely.
```

**Prompt:** 
```
Can I use the 'math' module in my current environment?
```

**Response:** 
```
Yes, the `math` module is **permitted**.

It is included in your current security whitelist and is safe for use in this context.
```

## Capabilities

### Audit Python code structure
Inspects the logic and syntax of a code string to find security holes.

### Block restricted modules
Prevents the use of dangerous libraries like os or subprocess.

### Identify dangerous functions
Flags calls to risky commands like eval or exec that could lead to exploits.

### Detect infinite loops
Finds logical patterns that would cause a script to run forever.

### Generate risk summaries
Turns technical audit findings into clear, readable security reports.

## Use Cases

### Automated Script Verification
A developer asks an agent to write a file cleanup script. The MCP flags the use of os.remove, preventing accidental data loss.

### Safe Agentic Workflows
An autonomous agent tries to run a complex data processing loop. The MCP catches a potential infinite loop before the process starts.

### Sandbox Environment Setup
A DevOps engineer uses the module whitelist to ensure an agent can only use math and json libraries, nothing else.

### Code Review Automation
A team uses the security summary to quickly vet large blocks of AI-suggested code during a pull request.

## Benefits

- Stop running unverified scripts by catching dangerous calls before execution.
- Prevent system compromise by blocking restricted modules like os and subprocess.
- Avoid system hangs by detecting infinite loop patterns in generated logic.
- Get clear risk assessments instead of digging through raw AST error logs.
- Enforce strict module permissions to keep your execution environment locked down.

## How It Works

The bottom line is you get a deterministic security check for every line of Python your agent generates.

1. Connect the MCP to your AI client through Vinkius.
2. Pass a string of Python code to your agent for inspection.
3. Receive a detailed security report or a simple pass/fail status.

## Frequently Asked Questions

**How does the Python Code Safety Linter protect my computer?**
It inspects the structure of Python code to find dangerous commands and restricted modules before you ever run the script, preventing accidental system changes or crashes.

**Can I use this Python Code Safety Linter to check code in Claude or Cursor?**
Yes. Once you connect this MCP to your AI client like Claude or Cursor, your agent can automatically audit any Python code it generates for you.

**Does the Python Code Safety Linter actually run the code?**
No. It uses AST traversal to look at the code's structure. This means it can safely inspect code without the risk of executing any dangerous commands.

**Will this MCP catch infinite loops in my Python scripts?**
Yes. It analyzes the logic of the code to identify patterns, such as 'while True' loops, that could cause your system to hang.

**How do I restrict which Python libraries my AI agent can use?**
You can use the module whitelist capability to define exactly which libraries are allowed, ensuring your agent stays within safe boundaries.

**How does the linter detect security risks?**
The linter uses AST (Abstract Syntax Tree) traversal to inspect the code's structure. This allows it to identify restricted imports and dangerous function calls without actually running the code.

**What is the difference between the security tiers?**
The server supports different strictness levels: Strict Tier (no restricted modules or dangerous functions), Standard Tier (allows limited filesystem access), and Development Tier (for internal testing).

**Can I use this to prevent infinite loops?**
Yes, the `analyze_code_safety` tool inspects `While` nodes to detect loops that lack a logical exit condition, helping prevent Denial of Service risks.