Mind Keg FAQs

Question 1

Which AI coding agents are compatible with Mind Keg?

Accepted Answer

Mind Keg is compatible with any MCP (Model Context Protocol)-compatible agent, including popular tools like Claude Code, Cursor, Windsurf, Codex CLI, Gemini CLI, and GitHub Copilot.

Question 2

What kind of information can Mind Keg store?

Accepted Answer

Mind Keg stores pre-curated 'atomic learnings' (max 500 characters each) such as debugging insights, architectural decisions, codebase conventions, and 'gotchas', categorised and tagged for easy access.

Question 3

How does Mind Keg help AI coding agents retain context?

Accepted Answer

It functions as a centralized brain, allowing agents to store 'atomic learnings' (max 500 chars) and retrieve them via semantic or keyword search, injecting past discoveries directly into new conversations for improved awareness.

Question 4

What is Mind Keg and its primary purpose?

Accepted Answer

Mind Keg is a persistent memory server for AI coding agents that prevents context loss. It stores critical knowledge like debugging insights and architectural decisions, making them available across different agent sessions.

Question 5

Does Mind Keg offer flexible search options for stored knowledge?

Accepted Answer

Yes, it supports robust semantic search using FastEmbed (local, free) or OpenAI (paid for best quality), and also provides a keyword-only search fallback via SQLite FTS5 for zero external dependencies.

Mind Keg

Mind Keg

主要功能

使用案例

主要功能

使用案例