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Memorine

Human-like memory for AI agents. Facts, events, procedures, contradiction detection, forgetting curve, and cross-agent sharing. Pure Python + SQLite.

v0.1.0
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Description


name: memorine description: Human-like memory for AI agents. Facts, events, procedures, contradiction detection, forgetting curve, and cross-agent sharing. Pure Python + SQLite. version: 0.2.0 metadata: openclaw: requires: bins: - python3 install: - kind: uv package: memorine bins: [memorine] entry: uv run python -m memorine.mcp_server homepage: https://github.com/osvfelices/memorine

Memorine

Persistent memory for OpenClaw agents. No APIs, no Docker, no external services. Just Python and SQLite.

What it does

  • Facts -- store, recall, and search with full-text search (FTS5). Near-duplicates are reinforced, contradictions are flagged automatically.
  • Forgetting curve -- memories decay over time if not accessed, just like human memory. Old garbage cleans itself up.
  • Events -- log what happened with causal chains (this caused that, which caused this other thing).
  • Procedures -- track multi-step workflows, learn which steps tend to fail, anticipate what you will need before starting a task.
  • Cross-agent sharing -- agents share facts with each other or the whole team through the same database.
  • Semantic search (optional) -- install memorine[embeddings] to add meaning-based search on top of keyword search.

14 MCP tools

Once installed, your agents get access to:

Tool What it does
memorine_learn Store a fact. Detects contradictions.
memorine_learn_batch Batch-learn multiple facts at once.
memorine_recall Search memory by query. Ranked by importance and recency.
memorine_log_event Record an event. Supports causal chains.
memorine_events Search past events by text or tags.
memorine_share Share a fact with another agent or the team.
memorine_team_knowledge Get collective knowledge across agents.
memorine_profile Full cognitive profile of what an agent knows.
memorine_anticipate Predict what you need for a task before starting.
memorine_procedure_start Start tracking a procedure.
memorine_procedure_step Log a step result in a running procedure.
memorine_procedure_complete Mark a procedure as done.
memorine_correct Fix a fact that turned out to be wrong.
memorine_stats Database stats: facts, events, procedures, db size.

Setup

Install Memorine:

pip install memorine

Add the MCP server to your OpenClaw config (openclaw.json):

{
  "mcpServers": {
    "memorine": {
      "command": "python3",
      "args": ["-m", "memorine.mcp_server"]
    }
  }
}

Allow the tools for your agents:

{
  "tools": {
    "allow": [
      "memorine_learn",
      "memorine_recall",
      "memorine_log_event",
      "memorine_events",
      "memorine_share",
      "memorine_team_knowledge",
      "memorine_profile",
      "memorine_anticipate",
      "memorine_procedure_start",
      "memorine_procedure_step",
      "memorine_procedure_complete",
      "memorine_correct",
      "memorine_stats",
      "memorine_learn_batch"
    ]
  }
}

Optional semantic search (adds meaning-based matching on top of keyword search):

pip install memorine[embeddings]

Security

Each agent can only modify its own data. Forget, correct, link, and procedure operations all validate ownership. No agent can touch another agent's memories.

How it works

Everything lives in a single SQLite file at ~/.memorine/memorine.db. FTS5 handles keyword search, triggers keep indexes in sync, and WAL mode allows concurrent reads. The forgetting curve uses retention = e^(-days / stability) where stability grows each time a memory is accessed. No LLM needed for any of this.

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Pricing

Free

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