Memex FAQs

Question 1

What is Memex and what problem does it solve?

Accepted Answer

Memex is a local-first, temporal knowledge graph memory layer for AI agents. It provides persistent, searchable, and graph-structured memory with temporal awareness, helping agents understand context and evolve information over time.

Question 2

How does Memex ensure privacy and local control?

Accepted Answer

It runs as a single Go binary with embedded SQLite, works out-of-the-box with local Ollama models, and keeps all data on your machine, ensuring privacy without needing external API keys for core operations.

Question 3

What kind of retrieval capabilities does Memex offer?

Accepted Answer

Memex uses advanced hybrid retrieval, combining BM25, vector search, and graph traversal with Reciprocal Rank Fusion (RRF). It also features temporal path queries, PageRank scoring, and community expansion for rich context.

Question 4

How does Memex manage changes and prevent duplicate information in the knowledge graph?

Accepted Answer

It employs a temporal knowledge graph core with bitemporal modeling and relation strengthening. Instead of creating duplicate edges, Memex increases the confidence (weight) of existing relations when facts are re-observed, preserving historical context while evolving knowledge.

Question 5

Can Memex integrate with my existing AI development workflow?

Accepted Answer

Yes, Memex offers multiple interfaces including a full Model Context Protocol (MCP) server, HTTP API, and interactive TUI. It also provides one-command integration with popular AI editors (e.g., VS Code, Cursor) for automatic memory capture.

Memex

Memex

Key Features

Use Cases

Key Features

Use Cases