Mimir: Local persistent memory for AI agents

Mimir: Local Persistent Memory for AI Agents

Mimir is an MCP-native solution designed to provide AI agents with robust, local persistent memory. Built with developers in mind, it leverages SQLite and FTS5 to ensure efficient data storage and retrieval, enabling agents to maintain context and learn from past interactions without relying on external cloud services. This makes it ideal for applications requiring privacy, offline functionality, or fine-grained control over data.

What Mimir Does

Mimir acts as a local database for your AI agents, allowing them to store and access information over time. This persistent memory is crucial for agents that need to remember user preferences, conversation history, learned facts, or any other data relevant to their ongoing operation. By using SQLite, Mimir offers a reliable and widely supported database solution, while FTS5 provides powerful full-text search capabilities, allowing agents to quickly find relevant information within their memory.

Key Features

• MCP-Native: Seamless integration with the MCP ecosystem.
• Fully Local: All data is stored on the user's machine, ensuring privacy and offline access.
• SQLite Backend: Utilizes a robust and widely adopted relational database for data storage.
• FTS5 Integration: Enables efficient and fast full-text searching of stored data.
• Persistent Memory: Allows AI agents to retain information across sessions.

Who Mimir is For

Mimir is specifically designed for AI developers building agents that require persistent storage and efficient data retrieval. This includes:

• Developers creating chatbots that need to remember past conversations.
• Researchers building AI models that require long-term memory for learning.
• Application developers integrating AI agents into desktop or offline environments.
• Anyone prioritizing data privacy and local control for their AI applications.