memodb-io/memobase

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

2862 stars · 231 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Memobase is a user profile-based long-term memory system for LLM applications, providing per-user profiles and event timelines that chatbots can query with low latency. It ships client SDKs for Python, TypeScript, and Go, an MCP server, and can be self-hosted or used as a hosted service.

Use cases

• add long-term memory to my ai chatbot
• remember user preferences across chat sessions
• build a personalized ai companion that remembers users
• store and retrieve user profiles for llm apps
• give my assistant memory without building a rag pipeline
• track user event timelines for personalization

When to choose

• you need persistent, structured user memory for chatbots or companions
• you want low-latency memory access without heavy pre-processing
• you care about keeping LLM memory costs low with batched processing

When to avoid

• you need a general-purpose vector search or document RAG engine
• you only need short-term conversation context within a single session
• you require a fully offline solution with no external service dependency

Facets

service · maturity active

rag llm-inference agent-framework database sdk artificial-intelligence large-language-models chatbots python go self-hosted long-term-memory user-profiles llm-memory ai-companion mcp memory-system retrieval-augmented-generation ai-agents nodejs docker

Member repositories

For agents

markdown · JSON · MCP: product_card(name="memodb-io/memobase")