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Kept is a local-first AI chat archiving tool that captures conversations from multiple popular LLM providers and stores them as plain markdown files on your filesystem. With powerful full-text and semantic search, knowledge graph integration, and code execution capabilities, Kept is ideal for developers, researchers, and privacy-conscious users seeking full control over their AI chat data.
Description
Kept: is an AI chat and productivity tool on your local archive. Captures conversations from ChatGPT, Claude, Gemini, Grok, and Kimi as Obsidian compatible markdown on your filesystem, with full-text search, knowledge graph, and an MCP servers. MIT license. View your Vault locally,
Detailed Description
Kept is a powerful local archive tool designed specifically for capturing and managing AI conversations from popular large language model (LLM) providers such as ChatGPT, Claude, Gemini, Grok, and Kimi. Its core purpose is to enable users to securely store their AI chat histories directly on their own filesystem as plain markdown files, eliminating the need for cloud storage and enhancing privacy and data control. By archiving conversations locally, Kept provides a highly accessible, readable, and searchable record of interactions with various AI models, making it an indispensable tool for developers, researchers, and AI enthusiasts who want to maintain an organized and permanent log of their AI dialogues. Kept’s feature set is robust and tailored for advanced usage. It supports a local-first approach, meaning all data is stored on the user’s device, ensuring full ownership and privacy. Conversations are saved as individual markdown files, which are human-readable and easily editable or shareable. The tool integrates SQLite FTS5 full-text search, allowing users to quickly find specific content across all archived chats. Beyond simple keyword search, Kept offers semantic recall capabilities, enabling context-aware retrieval of relevant conversations or information based on meaning rather than just exact text matches. Additionally, it incorporates a knowledge graph feature that helps visualize and connect concepts or topics discussed across multiple chats, providing a richer understanding of accumulated knowledge. Kept also supports an MCP (Message Control Protocol) server, which facilitates real-time interaction and management of chat data. This server capability allows for more dynamic workflows, including code execution within the environment, which can be particularly useful for developers who want to automate or extend the tool’s functionality. The entire project is open source and distributed under the MIT license, encouraging community contributions and transparency. This tool is best suited for users who regularly engage with multiple LLM providers and need a centralized, local repository for their AI conversations. Researchers and data scientists can benefit from Kept’s semantic search and knowledge graph to analyze trends and insights from their AI interactions. Developers working on AI applications will appreciate the code execution and MCP server support for integrating Kept into their development pipelines. Privacy-conscious users who prefer to avoid cloud-based storage will find Kept’s local-first design especially appealing. Kept is available for free under the MIT license, with no cost to download or use. It supports major operating systems including Windows, macOS, and Linux, with multiple installation options such as executable files, AppImage, and Debian packages. This accessibility ensures users across platforms can easily adopt the tool without licensing fees or subscription plans. Compared to alternatives that often rely on cloud storage or proprietary platforms, Kept stands out by prioritizing local data control and open-source transparency. While some competitors offer integrated AI chat management, they may lack Kept’s comprehensive markdown-based archival system, semantic recall, and knowledge graph features. However, users should note that Kept requires some technical familiarity to set up and leverage advanced features like the MCP server and code execution, which might present a learning curve for casual users. In summary, Kept is a sophisticated, privacy-focused AI conversation archive tool that excels in providing local, searchable, and semantically rich storage of chats from multiple LLM providers. Its open-source nature, cross-platform support, and developer-friendly features make it an excellent choice for professionals and enthusiasts who demand full control and deep insight into their AI interactions. Potential users should consider their technical comfort level and specific needs when choosing Kept over more turnkey cloud-based solutions.
Tool Features
- Local-first AI conversation archive
- Captures conversations from multiple LLM providers
- Stores chats as plain markdown files on filesystem
- SQLite FTS5 full-text search
- Semantic recall
- Knowledge graph integration
- MCP server support
- Code execution
Description
Kept is a local-first AI chat archiving tool that captures conversations from multiple popular LLM providers and stores them as plain markdown files on your filesystem. With powerful full-text and semantic search, knowledge graph integration, and code execution capabilities, Kept is ideal for developers, researchers, and privacy-conscious users seeking full control over their AI chat data.
Kept: is an AI chat and productivity tool on your local archive. Captures conversations from ChatGPT, Claude, Gemini, Grok, and Kimi as Obsidian compatible markdown on your filesystem, with full-text search, knowledge graph, and an MCP servers. MIT license. View your Vault locally,
Detailed Description
Kept is a powerful local archive tool designed specifically for capturing and managing AI conversations from popular large language model (LLM) providers such as ChatGPT, Claude, Gemini, Grok, and Kimi. Its core purpose is to enable users to securely store their AI chat histories directly on their own filesystem as plain markdown files, eliminating the need for cloud storage and enhancing privacy and data control. By archiving conversations locally, Kept provides a highly accessible, readable, and searchable record of interactions with various AI models, making it an indispensable tool for developers, researchers, and AI enthusiasts who want to maintain an organized and permanent log of their AI dialogues. Kept’s feature set is robust and tailored for advanced usage. It supports a local-first approach, meaning all data is stored on the user’s device, ensuring full ownership and privacy. Conversations are saved as individual markdown files, which are human-readable and easily editable or shareable. The tool integrates SQLite FTS5 full-text search, allowing users to quickly find specific content across all archived chats. Beyond simple keyword search, Kept offers semantic recall capabilities, enabling context-aware retrieval of relevant conversations or information based on meaning rather than just exact text matches. Additionally, it incorporates a knowledge graph feature that helps visualize and connect concepts or topics discussed across multiple chats, providing a richer understanding of accumulated knowledge. Kept also supports an MCP (Message Control Protocol) server, which facilitates real-time interaction and management of chat data. This server capability allows for more dynamic workflows, including code execution within the environment, which can be particularly useful for developers who want to automate or extend the tool’s functionality. The entire project is open source and distributed under the MIT license, encouraging community contributions and transparency. This tool is best suited for users who regularly engage with multiple LLM providers and need a centralized, local repository for their AI conversations. Researchers and data scientists can benefit from Kept’s semantic search and knowledge graph to analyze trends and insights from their AI interactions. Developers working on AI applications will appreciate the code execution and MCP server support for integrating Kept into their development pipelines. Privacy-conscious users who prefer to avoid cloud-based storage will find Kept’s local-first design especially appealing. Kept is available for free under the MIT license, with no cost to download or use. It supports major operating systems including Windows, macOS, and Linux, with multiple installation options such as executable files, AppImage, and Debian packages. This accessibility ensures users across platforms can easily adopt the tool without licensing fees or subscription plans. Compared to alternatives that often rely on cloud storage or proprietary platforms, Kept stands out by prioritizing local data control and open-source transparency. While some competitors offer integrated AI chat management, they may lack Kept’s comprehensive markdown-based archival system, semantic recall, and knowledge graph features. However, users should note that Kept requires some technical familiarity to set up and leverage advanced features like the MCP server and code execution, which might present a learning curve for casual users. In summary, Kept is a sophisticated, privacy-focused AI conversation archive tool that excels in providing local, searchable, and semantically rich storage of chats from multiple LLM providers. Its open-source nature, cross-platform support, and developer-friendly features make it an excellent choice for professionals and enthusiasts who demand full control and deep insight into their AI interactions. Potential users should consider their technical comfort level and specific needs when choosing Kept over more turnkey cloud-based solutions.
Frequently Asked Questions
What is Kept?
Kept is a local archive tool that captures and stores AI conversations from popular large language models like ChatGPT, Claude, Gemini, Grok, and Kimi as plain markdown files on your local filesystem. It enables full-text search, semantic recall, and knowledge graph features to help users manage and explore their AI chat history.
How much does Kept cost?
Kept is completely free to use and open source, distributed under the MIT license. There are no subscription fees or paid plans.
Who is Kept best for?
Kept is best suited for developers, researchers, AI enthusiasts, and privacy-conscious users who regularly interact with multiple LLM providers and want a local, searchable archive of their AI conversations without relying on cloud storage.
What are the main features of Kept?
Key features include local-first storage of AI chats as markdown files, support for multiple LLM providers, SQLite FTS5 full-text search, semantic recall for context-aware retrieval, knowledge graph integration to visualize connections, MCP server support for real-time interaction, and code execution capabilities.
Does Kept offer a free trial?
Kept is open source and free to use, so there is no need for a trial period. Users can download and use the tool immediately at no cost.
What integrations does Kept support?
Kept integrates with several popular large language models including ChatGPT, Claude, Gemini, Grok, and Kimi. It also supports an MCP server for advanced interaction and code execution.
How does Kept work?
Kept captures conversations from supported LLM providers and saves each chat as a plain markdown file on your local filesystem. It indexes these files using SQLite FTS5 to enable fast full-text search and uses semantic recall and knowledge graph features to help users find and connect information across conversations. The MCP server allows for real-time management and code execution within the tool.
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