Open Source Python Projects
Discover 599 open source Python repositories from GitHub, each with an analysis of what it does, key features, use cases and alternatives. Python projects here are most often combined with LLM, AI and Machine Learning. Last updated October 3, 2026.
599 repositories · updated October 3, 2026
ASC: A Super Fast Android Decompiler for Mobile Reverse Engineering
ASC is an innovative and exceptionally fast Android decompiler front-end, specifically designed for mobile researchers and agents. It redefines traditional decompilation by directly querying compiled artifacts, offering on-demand code extraction and analysis without heavy preprocessing. This approach results in significantly reduced memory usage and lightning-fast performance, even on large APKs.
Open Index: A Deterministic Memory Layer for Your AI Agents
Open Index is a powerful tool for building domain-specific, accurate, and structured data that AI agents can effectively operate on. It enables the creation of a "brain," a searchable and continuously improving context graph tailored to any domain. This system ensures agents have access to reliable, up-to-date information, enhancing their capabilities and decision-making processes.
ctx-gate: LLM Context Gateway for Efficient Token Usage
ctx-gate is an LLM-agnostic context optimization proxy that reduces token consumption in AI interactions. It intelligently prunes conversation history and tool outputs, ensuring critical facts are retained without altering your workflow. Compatible with Anthropic and OpenAI APIs, ctx-gate helps developers manage LLM costs and maintain prompt fidelity.
tooltrim: Drastically Reduce LLM Agent Tool Output Tokens, Improve Accuracy
tooltrim provides drop-in compression for LLM agent tool outputs, drastically cutting tokens while often improving answer accuracy. This provider-agnostic solution offers content-aware compression, faithfulness benchmarks, and seamless integration with popular frameworks or as an OpenAI-compatible proxy.
AgentShield: Python Firewall for AI Agent Spend Control
AgentShield is a pure Python library designed to prevent runaway AI agents from exceeding budget limits. It offers 10 composable spend rules, evaluated in under 1ms, providing robust cost control. Although its core development has transitioned to sipi.bot, the AgentShield Python package remains available for existing users and its test fixtures are open-source.
Ferret MCP: AI-Powered Knowledge Extraction for Any Codebase
Ferret MCP is an MCP server designed to extract comprehensive knowledge from any codebase, combining static analysis with AI-powered deep interpretation. It provides detailed insights into architecture, patterns, dependencies, and API surface, delivering a senior engineer's analysis in seconds. This tool integrates seamlessly with various MCP clients, offering both free static analysis and advanced AI-driven reports.
Local LLM Linux Troubleshoot: An AI Agent for Linux Diagnostics
Local LLM Linux Troubleshoot is an AI-powered agent designed to diagnose and resolve issues on Linux systems. It leverages llama.cpp for local AI processing, offering system diagnostics, safe command execution, and support for Docker, CLI, and a web GUI. This tool provides a privacy-first approach to managing and troubleshooting your Linux environment.
OpenWorkProof: Verifiable Work Contracts for AI Agent Systems
OpenWorkProof is an open protocol designed to bring transparency and accountability to AI agent work. It establishes verifiable contracts for multi-agent systems, ensuring that tasks are authorized, executed within agreed scopes, and independently verifiable. This protocol addresses critical questions about authorization, execution evidence, and human acceptance in AI-driven workflows.
DA-Forge: Streamlining Declarative Agent Creation for Copilot Notebooks
DA-Forge is a Python-based tool by Microsoft designed to automate the creation and deployment of Declarative Agents for Copilot Notebooks. It significantly reduces the manual effort and time required to set up AI assistants with specific grounding references, transforming an 85-minute process into just a few minutes. This tool is essential for developers and researchers working with Copilot Notebooks and Declarative Agents.
Curie: Automated and Rigorous Scientific Experimentation with AI Agents
Curie is an innovative AI-agent framework designed for automating rigorous scientific experimentation. It streamlines the entire research lifecycle, from hypothesis formulation to result interpretation, ensuring precision, reliability, and reproducibility. This empowers scientists to accelerate their research processes significantly.
SkillSpector: NVIDIA's Security Scanner for AI Agent Skills
SkillSpector is a critical security scanner developed by NVIDIA for AI agent skills. It identifies vulnerabilities, malicious patterns, and various security risks, including prompt injection and data exfiltration, in skills for platforms like Claude Code, Codex, and MCP. This tool empowers developers and users to ensure the safety and integrity of AI agent environments before skill installation.
cc-polymath: Context-Efficient Skills for Claude Code Development
cc-polymath is an innovative GitHub repository offering a vast collection of atomic skills and workflows specifically designed for Claude Code. It addresses the challenge of providing comprehensive development knowledge without overwhelming the AI's context window. By employing a progressive discovery system, cc-polymath ensures context efficiency and high-quality skill access across a wide range of technical domains.