Labsco
MCP SERVER

GroundMemory

by huss-mo

Persistent memory for an assistant, kept in Markdown files on your own machine and shared by every MCP client you point at it.

Agent Memory
Summary
Memory you can open in a text editor.

The design choice that matters here is storage: memory is Markdown on disk, so you can read it, edit it, and check it into a repo, and the SQLite index is rebuilt around it rather than being the source of truth. Because the workspace is a directory rather than a hosted account, several clients can share one identity, and a second project just means a second directory.

What it is

A local-first memory server that gives an agent long-term facts, a user profile, an entity graph and daily logs that survive between sessions. Memory lives in readable Markdown — `MEMORY.md`, `USER.md`, `AGENTS.md`, `RELATIONS.md` and dated files under `daily/` — indexed in SQLite so the same workspace can be attached to Claude Desktop, Cursor, Cline or Open WebUI at once.

What you get
  • Load the whole memory context at the start of a session — long-term facts, user profile, agent instructions, relations and daily logs — with `memory_bootstrap`
  • Write a fact to a chosen tier with `memory_write`, so preferences and decisions go to long-term memory and progress notes go to the daily log
  • Search across tiers together or one at a time with `memory_read`, combining BM25 keyword scoring and vector similarity in a single ranked query
  • Record typed relationships between entities with `memory_relate`, with near-duplicate triples suppressed by cosine similarity
  • An optional `memory_list` tool, and a dispatcher mode that routes every action through a single `memory_tool` call for clients that do better with a small tool surface
Requirements

Nothing by default: with `provider: none` it runs on SQLite with FTS5 alone — no API key, no GPU, no extra dependencies. Python 3.12 or newer; the package is `groundmemory` (0.6.13 in pyproject) and `groundmemory-mcp` serves HTTP at `http://127.0.0.1:4242/mcp`, with stdio also supported. `docker compose up -d` gives the same endpoint. Semantic search is optional and takes a local sentence-transformers model or any OpenAI-compatible endpoint, configured through `GROUNDMEMORY_EMBEDDING__PROVIDER` and friends.

Setup effort

One command — pip install groundmemory && groundmemory-mcp