Mimirs FAQs

Question 1

What are the core features of Mimirs?

Accepted Answer

Key features include semantic code search, real-time indexing of conversation transcripts for cross-session memory, automatic generation of a structured project wiki, codebase structure understanding via dependency graphs, and the ability to leave persistent notes and checkpoints.

Question 2

What AI coding tools or IDEs does Mimirs integrate with?

Accepted Answer

Mimirs supports a wide range of AI coding clients, including Claude Code, Cursor, Windsurf, JetBrains (Junie), GitHub Copilot, and any other MCP (Model Context Protocol) client, enhancing their capabilities with persistent memory.

Question 3

How does Mimirs reduce token usage and improve response times?

Accepted Answer

By indexing your codebase with hybrid vector and BM25 search, Mimirs allows AI agents to efficiently find code by meaning. This replaces costly context stuffing, leading to up to a 76% reduction in tokens per prompt and faster response times (e.g., 12s to 3s).

Question 4

Is Mimirs private and easy to set up?

Accepted Answer

Yes, Mimirs is fully local and private. It runs on Bun and SQLite, requiring no API keys, cloud services, or Docker. Setup is a single command (`bunx mimirs init`) and it works with popular AI IDEs like Claude Code, Cursor, and GitHub Copilot.

Question 5

What is Mimirs and how does it help AI coding agents?

Accepted Answer

Mimirs provides AI coding agents with a persistent, searchable memory of your codebase. This significantly reduces token usage and response times by giving agents instant, relevant context, eliminating redundant searches and forgotten information.

Mimirs

Mimirs

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