How does Ambi protect my data and privacy?

Ambi is built for privacy: all data is processed locally on your machine, it operates without internet access, and includes built-in PII filtering to automatically remove sensitive information before storage.

What is Ambi and how does it help AI assistants?

Ambi is a local-first AI context manager that establishes a shared, consistent memory across all your AI assistants, ensuring they always understand your environment without repeated explanations.

Which AI tools can Ambi synchronize context for?

Ambi supports AI tools that integrate via the Model Context Protocol (MCP), such as Claude and Cursor, enabling universal context synchronization across them. It aims to support more tools over time.

What does 'local-first' mean for Ambi?

'Local-first' means all your data is processed, stored, and managed directly on your own machine. Ambi doesn't send your information to external servers, giving you full control and enhancing privacy.

Ambi

Name: Ambi
Author: VickCG

byVickCG

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生产力与工作流

开发者工具

数据科学与机器学习

Establishes a shared, local memory for AI assistants, automatically capturing ambient context from your environment to ensure consistent understanding.

Ambi solves the common frustration of repeatedly explaining context to different AI tools like Claude, ChatGPT, and Cursor. It functions as a 'Single Source of Truth' by continuously capturing and synchronizing local context, including clipboard content and file changes. This ensures your AI assistants always have access to your coding style, project details, and past decisions, allowing them to understand your current work without redundant explanations, all while prioritizing privacy with local processing and PII filtering.

主要功能

010 GitHub stars

02Universal context synchronization across multiple AI tools

03Local-first design with all data processed and stored on your machine

04Privacy protection through built-in PII filtering before storage

05Time-aware memory prioritizing recent information for relevance

06Direct integration with AI tools via Model Context Protocol (MCP) support

使用案例

01Reducing repetitive explanations and prompts when switching between different AI tools.

02Maintaining consistent project context across various AI assistants (e.g., Claude, ChatGPT, Cursor).

03Providing a local, privacy-protected memory layer for AI interactions and development workflows.