Python Code Safety Linter Connector for AI agents.
3 live capabilities
Secure your Python execution environment from unsafe AI-generated code
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Why people use Python Code Safety Linter
Preventing Python vulnerabilities with Python Code Safety Linter
With this MCP, that workflow changes. Instead of blind trust, you have a structural audit. Your agent can now run a check that looks at the actual logic of the code. You get a clear answer on whether the script is safe to run, turning a high-stakes gamble into a controlled, repeatable process.
What Vinkius changes
You get a deterministic security check for every line of Python your agent generates.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 6,100+ Connectors
- Real-world use case 01
Automated Script Verification
A developer asks an agent to write a file cleanup script.
- Real-world use case 02
Safe Agentic Workflows
An autonomous agent tries to run a complex data processing loop.
- Real-world use case 03
Sandbox Environment Setup
A DevOps engineer uses the module whitelist to ensure an agent can only use math and json libraries, nothing else.
Complete set · 3capabilities
The complete Python Code Safety Linter capability set.
These are the exact actions your AI can choose when you ask it to work with Python Code Safety Linter.
01—03
3 capabilities in this set.
Part of 3 available through Python Code Safety Linter.
- 01 Capability
Analyze code safety
Performs a full security audit of Python code using AST traversal. It catches dangerous functions and module imports.
- 02 Capability
Check module whitelist
Checks if a specific Python module is allowed in your current security context. It helps enforce strict environment rules.
- 03 Capability
Summarize security report
Converts technical audit data into a clear summary. It makes it easy to understand the risks found in a script.
Set up in minutes
One URL. Then ask Python Code Safety Linter to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Python Code Safety Linter from the conversation.
Choose your client
Live previewAdvanced clients IDE · CLI
Claude · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_x1ckNcFBAQnapMBxq8ev6N59e1TC0dLuvgwnqp8a/mcp - Step 01
Open Connectors
In Claude Web or Claude Desktop, open Settings and choose Connectors.
- Step 02
Add the URL
Choose Add custom connector, name it Python Code Safety Linter, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Python Code Safety Linter for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_x1ckNcFBAQnapMBxq8ev6N59e1TC0dLuvgwnqp8a/mcp - Step 01
Open MCP settings
On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
- Step 02
Add the URL
Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the Python Code Safety Linter URL.
- Step 03
Save and start
Save the connection and enable Python Code Safety Linter in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"python-code-safety-linter": {
"url": "https://edge.vinkius.com/vk_preview_x1ckNcFBAQnapMBxq8ev6N59e1TC0dLuvgwnqp8a/mcp"
}
}
}- Step 01
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
- Step 02
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
- Step 03
Save the file
Cursor will automatically detect the new Connector
- Step 04
Start using Python Code Safety Linter
Open Agent mode in chat and ask: "Using Python Code Safety Linter, help me...". 3 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"python-code-safety-linter": {
"url": "https://edge.vinkius.com/vk_preview_x1ckNcFBAQnapMBxq8ev6N59e1TC0dLuvgwnqp8a/mcp"
}
}
}- Step 01
Create MCP config
Create a .vscode/mcp.json file in your project root
- Step 02
Add the server config
Paste the JSON configuration above
- Step 03
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
- Step 04
Start using Python Code Safety Linter
Ask Copilot: "Using Python Code Safety Linter, help me...". 3 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"python-code-safety-linter": {
"url": "https://edge.vinkius.com/vk_preview_x1ckNcFBAQnapMBxq8ev6N59e1TC0dLuvgwnqp8a/mcp"
}
}
}- Step 01
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
- Step 02
Add the server
Paste the JSON configuration above into mcp_config.json
- Step 03
Save and reload
Windsurf will detect the new server automatically
- Step 04
Start using Python Code Safety Linter
Open Cascade and ask: "Using Python Code Safety Linter, help me...". 3 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"python-code-safety-linter": {
"url": "https://edge.vinkius.com/vk_preview_x1ckNcFBAQnapMBxq8ev6N59e1TC0dLuvgwnqp8a/mcp"
}
}
}- Step 01
Open Cline MCP Settings
Click the Connectors icon in the Cline sidebar panel
- Step 02
Add remote server
Click "Add Connector" and paste the configuration above
- Step 03
Enable the server
Toggle the server switch to ON
- Step 04
Start using Python Code Safety Linter
Ask Cline: "Using Python Code Safety Linter, help me...". 3 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add python-code-safety-linter --transport http "https://edge.vinkius.com/vk_preview_x1ckNcFBAQnapMBxq8ev6N59e1TC0dLuvgwnqp8a/mcp"- Step 01
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
- Step 02
Add the Connector
Run the command above in your terminal
- Step 03
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
- Step 04
Start using Python Code Safety Linter
Ask Claude: "Using Python Code Safety Linter, show me...". 3 tools are ready
Where the request belongs
Work Python Code Safety Linter can move forward.
This is for developers and DevOps engineers who use AI to automate scripting but don't want to risk running unverified code on their local machines or production servers.
DevOps Engineer
Ensures that automation scripts generated by agents don't accidentally wipe directories or leak credentials.
Python Developer
Uses the linter to quickly verify the safety of code snippets suggested by an AI assistant.
Security Researcher
Audits AI-generated code for vulnerabilities before integrating it into larger projects.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
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JSON Schema Validator
Validate JSON documents and lint schemas for structural integrity.
OOPSpam
Block spam submissions on your forms and comments with an AI-powered filter that catches bots without annoying real users.
X Ads (Twitter)
Connect your X Ads account to any AI agent. audit campaigns, analyze line item performance, and pull engagement reports through natural conversation.
Box
Store, share, and collaborate on files securely with enterprise-grade cloud content management and governance controls.
Bring your own AI
Change the model, client or framework. Keep Python Code Safety Linter connected.
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Claude -
ChatGPT -
Gemini -
Cursor -
VS Code -
Windsurf -
ZCode -
Cline -
Zed -
Continue -
Kiro -
Roo Code -
Zencoder -
Goose -
Void -
Augment Code -
Amp -
Qodo -
Tabnine -
Pieces -
Sourcegraph Cody -
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Amazon Q -
Antigravity -
BoltAI -
Raycast -
Jan -
LM Studio -
AnythingLLM -
Open WebUI -
Msty -
Cherry Studio -
LibreChat -
TypingMind -
Chorus -
5ire -
n8n -
LangChain -
LlamaIndex -
CrewAI -
Vercel AI SDK
Before you connect
Questions about Python Code Safety Linter.
The practical details behind the request, access and result.
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 capability inspects While nodes to detect loops that lack a logical exit condition, helping prevent Denial of Service risks.
One connection away
Give your agent a direct line to Python Code Safety Linter.
Connect Python Code Safety Linter once. Keep it beside 6,100+ managed Connectors when the next task needs more.
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