Ross ROSS = Recommend OSS · open-source software intelligence for agents

aiming-lab/SimpleMem

SimpleMem: Efficient Lifelong Memory for LLM Agents — Text & Multimodal observed · 2026-08-28

github.com/aiming-lab/SimpleMem · Python · MIT (permissive) observed · 2026-08-28

Health v2 · maintenance only

71/100

  • Activity 94
  • Release rhythm 72
  • Longevity 17
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: 36.0
  • age_days: 244
  • days_rel: 104
  • days_push: 40
  • n_releases_24m: 3

Full methodology

Adoption not part of the score

3720 stars · 392 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

SimpleMem is a Python library and MCP server that provides efficient lifelong memory for LLM agents, storing, compressing, and retrieving long-term memories with semantic lossless compression. It supports text as well as multimodal inputs (image, audio, video) and integrates with any MCP-compatible client such as Claude Desktop, Cursor, and LM Studio.

Use cases

  • give my llm agent long-term memory across sessions
  • add persistent memory to a chatbot
  • store and retrieve conversation history for an ai assistant
  • compress agent memories without losing semantics
  • add multimodal memory for images, audio and video to an agent
  • run a memory mcp server for claude desktop or cursor
  • build a rag pipeline with semantic memory retrieval

When to choose

  • you need persistent, retrievable long-term memory for LLM agents
  • you want MCP integration with clients like Claude Desktop or Cursor
  • you need multimodal memory support beyond plain text
  • you want a lightweight Python package with MIT licensing

When to avoid

  • you only need short-term in-context memory within a single session
  • you need a fully managed hosted memory service rather than self-hosted components
  • your project is not Python-based and does not support MCP

Facets

library · maturity active

rag vector-database search-engine mcp agent-framework llm-inference compression large-language-models artificial-intelligence developer-tools python cross-platform self-hosted lifelong-memory semantic-search multimodal knowledge-graph agent-memory mcp-server memory-management ai-agents retrieval-augmented-generation natural-language-processing

2 sources

Member repositories

RepositoryRoleHealth v2
aiming-lab/SimpleMemmain71

For agents

markdown · JSON · MCP: product_card(name="aiming-lab/SimpleMem")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem