12 Repos
Systems for applying fine-grained authorization logic to artificial intelligence model usage.
Distinguishing note: Focuses on authorization for AI tool execution.
Explore 12 awesome GitHub repositories matching artificial intelligence & ml · AI Access Control. Refine with filters or upvote what's useful.
Tailscale is a zero-trust networking overlay that connects distributed devices and services into a private, encrypted mesh network. By utilizing a high-performance, user-space implementation of the WireGuard protocol, it establishes secure peer-to-peer tunnels across diverse network topologies without requiring complex firewall configuration. The platform operates on a centralized control plane that manages global network state, authentication, and policy distribution, ensuring that connectivity is governed by identity rather than traditional IP-based rules. What distinguishes Tailscale is it
Performs fine-grained access control decisions on model usage and tool execution.
Lens is a multi-cluster management platform and desktop application for administering Kubernetes environments. It provides a graphical interface for deploying Helm charts, editing YAML manifests, and managing the lifecycle of pods and deployments. The project features an AI-powered cluster assistant that enables users to query cluster state, perform autonomous troubleshooting, and translate natural language requests into system commands. It also supports collaborative team access through shared spaces, utilizing encrypted cluster sharing and role-based access control to manage credentials and
Allows administrators to toggle the availability of AI-powered assistance for users.
FastMCP is a Python framework designed for building servers that expose functions, resources, and prompts to AI models using the Model Context Protocol. It simplifies the development process by automatically deriving tool metadata, input schemas, and documentation directly from Python function signatures and type hints. The framework provides a unified container for managing these components, allowing developers to build modular applications that integrate seamlessly with AI assistants. The project distinguishes itself through its support for interactive, server-defined user interface compone
Manages authentication, authorization, and access control for AI-accessible tools using OAuth, OIDC, and granular policy enforcement.
unopim is an AI-powered product information management system that serves as a centralized repository for managing product attributes, categories, and variations. It functions as a containerized product repository and a multi-channel data distributor, synchronizing consistent product information and pricing across diverse external sales platforms and marketplaces. The platform distinguishes itself through an LLM-based catalog manager that provides a conversational interface for executing data management tasks. This allows users to perform item creation, content enrichment, and quality scans u
Limits agent behavior through token budgets, step counts, and confidence-based approval queues to ensure AI governance.
This project is a command line interface and GitHub CLI extension that functions as an AI coding agent and model orchestrator. It enables the writing of code and the management of repositories through natural language prompts using large language models. The tool implements the Agent Client Protocol to act as a standardized agent server for external editors. It features a provider-agnostic routing system that allows switching between different hosted AI models or external compatible endpoints. Capabilities include the automation of Git workflows, such as managing pull requests and issues, an
Governs the availability and access of specific AI models and features across an organization.
Higress is an AI API gateway and cloud-native traffic manager that functions as a Kubernetes ingress controller. It provides a centralized system for routing, securing, and optimizing traffic directed toward large language models, AI agents, and microservice architectures. The project distinguishes itself through deep AI orchestration, including the ability to host and manage Model Context Protocol servers that transform REST APIs into tools for AI agents. It features specialized AI infrastructure for model request proxying, protocol translation across multiple providers, and semantic-based c
Provides fine-grained authorization logic to restrict access to specific AI tools based on whitelists or role-based headers.
This repository contains the comprehensive documentation for a code editor focused on AI-assisted software development and remote development workflows. It covers the implementation of AI agents and language models used for autonomous code generation, large-scale refactoring, and task iteration. The project is distinguished by its deep integration of autonomous AI agents capable of web navigation, application logic validation, and orchestrating multi-step development processes. It provides specialized frameworks for tailoring AI behavior through custom instructions, model context protocols, a
Implements controls to manage AI agent independence through manual approval queues or full autonomous iteration.
PraisonAI is an autonomous AI agent platform that coordinates multiple LLM-powered agents for research, planning, and execution of complex workflows. It functions as a multi-agent orchestration framework, a workflow builder, and a Model Context Protocol server, while also providing retrieval-augmented generation through vector knowledge bases. Agents can interact via CLI, web, or standardized protocols with sandboxed code execution. The platform distinguishes itself with a rich set of agent communication protocols, including A2A, REST, WebSocket, voice and telephony integration, and MCP, allo
Controls whether the AI agent requires user approval before editing files or running commands.
This project is a comprehensive collection of Python programming education materials, including tutorials, exercises, and curated code samples. It serves as a learning curriculum and software engineering toolkit, utilizing Jupyter Notebooks to combine executable code with descriptive educational text. The repository provides practical implementation guides for building large language model applications, such as retrieval-augmented generation systems, stateful AI agents, and machine learning workflows. It distinguishes itself by offering a structured approach to agentic coding workflows, cover
Configures AI agent autonomy levels and human-in-the-loop approval queues for executing shell commands.
Axonhub is an AI gateway and multi-model API proxy that provides a unified interface for routing requests to multiple large language model providers. It functions as a load balancer and translation layer, converting a standardized API format into provider-specific payloads to enable communication with various AI models without provider-specific code. The system manages traffic through rule-based routing and automatic failover to maintain high availability. It differentiates its operations by providing a provider-agnostic interface that decouples client requests from specific model backends us
Applies fine-grained authorization logic and usage quotas to secure AI model access via API keys.
This project is a Telegram bot bridge that connects the Telegram chat interface to large language models. It functions as a relay that routes user prompts to an artificial intelligence service and returns the generated text responses to the user. The application uses session token authentication to access language model services via browser-extracted cookies. Access to the bot is managed through a whitelist controller that restricts interactions to a predefined list of authorized user identifiers. The system is designed for containerized deployment to ensure consistent execution across diffe
Restricts access to the AI model using a whitelist of authorized user identifiers.
mini-swe-agent is an autonomous software engineering system designed to develop features and fix bugs by combining large language models with a bash interface. It operates as an agentic framework that executes coding tasks and documentation updates through a continuous cycle of model reasoning and tool execution. The project differentiates itself with a strong focus on safety and evaluation, utilizing container-based sandbox execution via Docker or Singularity to isolate command execution. It includes a batch-parallel evaluation harness to measure code-fixing accuracy against standardized sof
Limits AI agent autonomy using step counts, budget ceilings, and human-in-the-loop approval queues.