Open Source Privacy Tools
Privacy is the ability to control how personal information is collected, used, stored, and shared. Privacy-focused technology helps reduce tracking, limit unnecessary data collection, protect communications and files, and keep sensitive activity out of third-party services. It can also give people more choice over where their data lives and how long it is retained, whether they are browsing, collaborating, or using digital services offline.
Open source privacy tools include browsers, content blockers, encrypted communication and collaboration software, local-first apps, and utilities for securing data. When choosing one, consider its security model, maturity, maintenance activity, license, platform requirements, and compatibility with services you already use. Check whether its privacy claims match how it handles data in practice. These tools are useful to individuals, organizations, and developers seeking greater transparency and control over personal or sensitive information.
104 repositories · updated October 4, 2026
agent-observability: Monitor AI Coding Agents Locally
A self-hosted OpenTelemetry stack for monitoring Claude Code and OpenAI Codex. It routes telemetry to Prometheus, Loki, and Tempo, then presents usage, performance, and activity in Grafana dashboards.
SwarmLLM: Run Local and Distributed AI Models
SwarmLLM runs open AI models on your computer and can pool resources with other computers to run larger models. It also provides OpenAI- and Anthropic-compatible APIs for local apps and agents.
AgentAleph: Run a Local Coding Agent and Manage GGUF Models
Agent Aleph is a Linux desktop app for running local GGUF models and using them to inspect, edit, and build software projects. It combines model downloads and inference controls with an approval-based coding agent.
maskit: Locally Mask Sensitive Data Before AI Requests
Maskit is a local privacy gateway that replaces sensitive information in AI requests with consistent placeholders, then restores it in responses. It is aimed at developers using AI coding tools or web assistants who want a configurable layer between their data and model providers.
AI-Engineering-Coach: Analyze AI Coding Assistant Usage
AI Engineer Coach analyzes local session logs from AI coding assistants and presents practice, activity, and output insights in a dashboard. It suits developers who want to improve agentic workflows while keeping session data on their machine.
holaOS: Build a Local-First Workspace for AI Agents
holaOS is an Electron workspace that brings agents, apps, integrations, chat tools, and shared memory together on your machine. It suits teams that want to connect existing systems and choose their own agents or models.
OGAD: Run Private AI Models on Your Desktop
OGAD is a desktop AI studio and local runtime for running text, vision, image, and speech models on your own hardware. It also provides an OpenAI-compatible local API, with optional Pro features for on-device memory and activity capture.
deja-vu: Search Coding Agent Session History
deja-vu indexes existing coding-agent conversations into a shared, local search tool. It helps developers recover past decisions, fixes, and commands across supported agents without requiring an LLM or embedding service.
meetily: Transcribe and Summarize Meetings Locally
Meetily is a Rust-based desktop meeting assistant that records audio, transcribes it locally, and creates AI summaries. It suits people who want control over meeting data and can run local speech and language models.
mityu: Transcribe and Summarize Meetings Locally
Mityu is a desktop meeting assistant that transcribes audio and creates source-linked summaries on your device. It suits people who need private meeting notes without a required cloud service, with Windows currently the published release platform.
cognithor: Run a Local Autonomous AI Agent
Cognithor is a Python agent operating system for running an assistant locally, connecting it to LLMs, messaging channels, memory, and tools. It suits users who want configurable personal automation and control over where their data is stored.
taOS: Run Self-Hosted AI Agents Across Your Hardware
taOS is a self-hosted platform for running AI agents, local models, chat, and memory on hardware you control. It combines a web desktop with optional distributed compute, making it suited to privacy-focused users who can manage a beta system.