Impact Preview
I

Impact Preview

Agent Polis is an impact preview system for AI agent actions, providing a function similar to 'Terraform plan'. It analyzes the impact of autonomous AI agents before they execute operations, displays a difference preview, and requires manual approval before execution, aiming to prevent AI agents from performing dangerous operations.
2 points
5.4K

What is Agent Polis Impact Preview?

Agent Polis is a security protection system for AI agent operations. Before an AI agent (such as Claude, Cursor, etc.) executes any action, it first analyzes the impact of the action, displays the specific changes, and waits for manual approval. This is like providing a 'preview mode' for AI operations, allowing you to know what changes will occur and avoid accidental damage.

How to use Agent Polis?

Using Agent Polis is very simple: 1) Install the MCP server and integrate it with your AI tools; 2) When an AI agent proposes an operation, the system will generate an impact preview; 3) You view the details of the changes and risk assessment in the interface; 4) Approve or reject the operation; 5) Only approved operations will be actually executed.

Applicable Scenarios

Suitable for all scenarios where AI agents are used for code development, system management, file operations, etc. Particularly suitable for: developers using AI assistants to edit code, operations staff using AI to manage configurations, teams requiring review of AI operations in collaboration, and projects with security requirements for the production environment.

Main Features

Impact Preview
Display file difference comparison, risk assessment, and warning information before the operation is executed, so that you clearly know what changes will occur.
Approval Workflow
Provide a complete approval process, support approving, rejecting, or modifying the operation suggestions proposed by the AI, and ensure that all operations are manually confirmed.
Risk Assessment
Automatically detect high-risk operations, such as modifying production database configurations, deleting system files, executing dangerous commands, etc., and provide risk level assessments.
Audit Trail
Record the historical records of all operations, including who proposed them, when they were proposed, whether they were approved, when they were executed, and other complete information, which is convenient for tracing and auditing.
SDK Integration
Provide simple decorators and client libraries, which are convenient to integrate into existing AI agent code. You can enable the approval process by adding just a few lines of code.
Visual Dashboard
A Web interface based on Streamlit, providing an intuitive operation management and approval interface, supporting batch operations and real-time status monitoring.
Advantages
Prevent accidental damage: Avoid data loss or system damage caused by AI misoperations.
Improve transparency: Clearly understand the content and impact of the operations that the AI is about to execute.
Enhance control: Manual approval ensures that all operations meet expectations and security requirements.
Easy to integrate: Support multiple AI tools and development environments, with simple configuration.
Free and open source: Under the MIT license, it can be freely used and modified.
Limitations
Requires manual intervention: Each operation needs to wait for approval, which may affect automation efficiency.
Learning cost: Requires certain configuration and integration work.
Relies on external tools: Needs to cooperate with AI tools that support the MCP protocol.
Early stage: Currently in the development stage, and the functions are still being continuously improved.

How to Use

Quick Installation
Install Agent Polis via pip and start the MCP server.
Configure AI Tools
Add server configuration in tools that support MCP, such as Claude Desktop or Cursor.
Start Using
When the AI assistant executes an operation, the system will automatically generate a preview and wait for approval.
Approve Operations
View, approve, or reject pending operations in the dashboard or API.

Usage Examples

Safely Modify Configuration Files
The AI assistant wants to modify the database configuration file, but is not sure if it is safe. Use Agent Polis to preview the changes and confirm that it will not accidentally point to the production environment.
Prevent Accidental File Deletion
The AI assistant suggests cleaning up temporary files, but may accidentally delete important files. Use Agent Polis to preview the deletion operation and confirm which files will be deleted.
Review Dangerous Commands
The AI assistant generates a complex shell command, and it is not sure if it is safe. Use Agent Polis to evaluate the command risk.

Frequently Asked Questions

Will Agent Polis affect the response speed of the AI assistant?
Which AI tools and platforms are supported?
How to customize risk assessment rules?
Does it support team collaboration and permission management?
What if the AI assistant bypasses Agent Polis and operates directly?

Related Resources

Official GitHub Repository
Get the latest source code, submit issues, and participate in development.
MCP Protocol Documentation
Understand the technical details and specifications of the Model Context Protocol.
Installation and Configuration Guide
Detailed installation steps and configuration instructions.
API Reference Documentation
Complete API interface description and usage examples.
Community Discussion
Communicate with other users about usage experiences and best practices.

Installation

Copy the following command to your Client for configuration
{
    "mcpServers": {
        "impact-preview": {
            "url": "http://localhost:8000/mcp"
        }
    }
}
Note: Your key is sensitive information, do not share it with anyone.

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