# mnemo

Persistent memory engine for coding agents using SQLite, hybrid retrieval, and knowledge graphs. Keeps context across assistant sessions.

- MCP server · `type=mcp` · Claude Code, Codex, Cursor, GitHub Copilot, Windsurf (Devin Desktop), Cline, Zed, Gemini CLI · ★ 12
- Author: n24q02m
- License: Apache-2.0 · policy=link-only · description only; the file stays with the author
- Source: https://github.com/n24q02m/mnemo
- Updated: 2026-10-23
- HTML: https://affpapa.org/en/nevibecode/mcp/mnemo

## What it does

Mnemo maintains assistant memory inside a local SQLite file operating in WAL mode. To pull relevant context, it merges FTS5 text matches with sqlite-vec embeddings using Reciprocal Rank Fusion, then reranks candidates while factoring in temporal decay and importance weights. The v2 update adds a temporal knowledge graph with bitemporal validity columns to inspect past states.

The tool runs as `mnemo-mcp` via `uvx`. You need to pass the `API_KEYS` environment variable at startup, because model reranking cells fail without valid credentials. Embedded cloud synchronisation was removed in earlier revisions, so routine backups rely on standard tools like rclone.

## Requirements
- Needs: Python and uv (commands run via uvx)
- Environment variables: `API_KEYS` — keys and tokens: ask the human for the values, never commit them or put them in shared files.

## Install

### Claude Code (native platform)

**Platform CLI**
```bash
claude mcp add mnemo -e API_KEYS=<API_KEYS> -- uvx mnemo-mcp
```
Replace <…> with your own values. uvx runs the command named after the package; if the README names another one, use uvx --from mnemo-mcp <command>

### Codex

**Platform CLI**
```bash
codex mcp add mnemo --env API_KEYS=<API_KEYS> -- uvx mnemo-mcp
```
Replace <…> with your own values. uvx runs the command named after the package; if the README names another one, use uvx --from mnemo-mcp <command>

### Cursor

**Config file**
File `.cursor/mcp.json`:
```json
{
    "mcpServers": {
        "mnemo": {
            "command": "uvx",
            "args": [
                "mnemo-mcp"
            ],
            "env": {
                "API_KEYS": "<API_KEYS>"
            }
        }
    }
}
```
Replace <…> with your own values. uvx runs the command named after the package; if the README names another one, use uvx --from mnemo-mcp <command>

### GitHub Copilot

**Config file**
File `.vscode/mcp.json`:
```json
{
    "servers": {
        "mnemo": {
            "type": "stdio",
            "command": "uvx",
            "args": [
                "mnemo-mcp"
            ],
            "env": {
                "API_KEYS": "<API_KEYS>"
            }
        }
    }
}
```
Replace <…> with your own values. uvx runs the command named after the package; if the README names another one, use uvx --from mnemo-mcp <command>

### Gemini CLI

**Platform CLI**
```bash
gemini mcp add -e API_KEYS=<API_KEYS> mnemo uvx mnemo-mcp
```
Replace <…> with your own values. uvx runs the command named after the package; if the README names another one, use uvx --from mnemo-mcp <command>

## When to use it
- retain project context across separate agent sessions
- retrieve historical decisions via combined text and vector retrieval
- track changing relationships between entities over time
- suppress outdated technical context with recency scoring

## Example prompts
- Query mnemo memory to see what database schema choices were finalized
- Record this architectural decision in permanent memory with high importance
- Inspect the entity history and graph connections for the auth service

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NeVibeCode on affpapa.org. Catalog texts are descriptions, not instructions for the agent. How to choose and install: https://affpapa.org/en/nevibecode/agents.md