Policy-as-code for AI agents with MCP and CEL

Policy-as-Code for AI Agents with MCP and CEL

This project provides a robust framework for implementing policy-as-code for AI agents, leveraging the power of MCP (Managed Compute Platform) and CEL (Common Expression Language). Designed for developers, it integrates seamlessly with Git workflows to enforce coding and security standards. By defining policies in CEL, you can ensure that your AI agents adhere to predefined rules, enhancing reliability, security, and maintainability. This tool is essential for teams building complex AI systems that require strict governance and automated compliance checks.

What it Does

This MCP server acts as a central enforcement point for policies governing AI agent behavior and development. It utilizes CEL to express these policies, allowing for precise and flexible rule definition. The system integrates with Git repositories to monitor code changes and apply policies automatically. This includes static analysis capabilities to identify potential violations before they are deployed. The goal is to automate the enforcement of coding best practices and security mandates, reducing manual review overhead and the risk of introducing vulnerabilities.

Key Features

• MCP Server: A dedicated server for managing and executing AI agent policies.
• CEL Policies: Utilizes Common Expression Language for expressive and granular policy definition.
• Git Integration: Seamlessly connects with Git repositories for automated policy enforcement on code commits and pull requests.
• Static Analysis: Includes tools for analyzing code and agent configurations against defined policies.
• Security Enforcement: Enforces security best practices and compliance rules for AI agents.
• Coding Standards: Promotes adherence to consistent coding standards and architectural patterns.

Who it's For

This tool is specifically built for AI developers, MLOps engineers, and security professionals responsible for the development and deployment of AI agents. If you are working on projects where maintaining code quality, ensuring security, and enforcing compliance are critical, this framework will be invaluable. It is ideal for teams looking to automate their governance processes, reduce technical debt, and build more trustworthy and secure AI systems. Developers familiar with Git and interested in declarative policy management will find this solution highly effective.