Code Memory FAQs

Question 1

What is Code Memory?

Accepted Answer

Code Memory is a code intelligence layer that provides AI coding assistants with a deep, structured understanding of your codebase. It acts as an MCP server, offering specialized tools for precise search, reference tracing, and Git history exploration.

Question 2

How does Code Memory improve AI assistant performance?

Accepted Answer

It eliminates context-window bloat and vague 'search everything' queries by routing requests through three purpose-built tools for code structure, documentation, and Git history, ensuring the AI gets the most relevant, targeted information.

Question 3

What types of search can Code Memory perform?

Accepted Answer

Code Memory offers hybrid retrieval (BM25 + dense vectors) for semantic and structural code search, definition finding, reference tracing, and exploring Git commit history to understand developer intent and debug regressions.

Question 4

Is Code Memory compatible with my existing AI development setup?

Accepted Answer

Yes, Code Memory integrates seamlessly as an MCP server with various AI assistant hosts, including Gemini CLI, Claude Desktop, and VS Code (for Copilot and Continue), augmenting their capabilities with deep codebase insights.

Question 5

Does Code Memory require an internet connection for indexing or searching?

Accepted Answer

No. Code Memory performs offline indexing and embedding generation using AST parsing and local `sentence-transformers`. All data is stored locally with `sqlite-vec`, ensuring privacy and fast access without an internet connection.

Code Memory

Code Memory

Key Features

Use Cases

Key Features

Use Cases