# ori-memory

Keeps agent memory available across sessions, clients, and machines, with search over linked knowledge. Useful when project context needs to outlast a single chat.

- MCP server · `type=mcp` · Claude Code, Codex, Cursor, GitHub Copilot, Windsurf (Devin Desktop), Cline, Zed, Gemini CLI · ★ 334
- Author: aayoawoyemi
- License: Apache-2.0 · policy=link-only · description only; the file stays with the author
- Source: https://github.com/aayoawoyemi/Ori-Mnemos
- Updated: 2026-10-01
- HTML: https://affpapa.org/en/nevibecode/mcp/ori-memory

## What it does

ori-memory stores information in Markdown files, connects notes with wiki-links, and uses Git for version control. An index is built from those files; the MCP server gives an agent access to it, including through the `ori_recall` tool. The same index can also be used from the CLI or the library.

Add the server with `claude mcp add ori-memory -- npx -y ori-memory`. To create an index from the CLI, run `npx ori init` and `npx ori index build`. Markdown files hold the underlying information, but learned retrieval state is stored separately, so export it before deleting data.

## Requirements
- Needs: Node.js (commands run via npx)

## Install

### Claude Code (native platform)

**Platform CLI**
```bash
claude mcp add ori-memory -- npx -y ori-memory
```

### Codex

**Platform CLI**
```bash
codex mcp add ori-memory -- npx -y ori-memory
```

### Cursor

**Config file**
File `.cursor/mcp.json`:
```json
{
    "mcpServers": {
        "ori-memory": {
            "command": "npx",
            "args": [
                "-y",
                "ori-memory"
            ]
        }
    }
}
```

### GitHub Copilot

**Config file**
File `.vscode/mcp.json`:
```json
{
    "servers": {
        "ori-memory": {
            "type": "stdio",
            "command": "npx",
            "args": [
                "-y",
                "ori-memory"
            ]
        }
    }
}
```

### Gemini CLI

**Platform CLI**
```bash
gemini mcp add ori-memory npx -y ori-memory
```

## When to use it
- keep agent memory across sessions
- find related facts in a knowledge graph
- connect shared memory to an MCP client
- build an index from Markdown files

## Example prompts
- Remember this decision about caching so I can retrieve it in a later session.
- Find what we decided about caching in the project memory.
- Show notes linked to the architecture decision.

## Similar
- [deep-agents-memory](https://affpapa.org/en/nevibecode/skills/deep-agents-memory.md) — skill · 19000 installs
- [memory-management](https://affpapa.org/en/nevibecode/skills/memory-management.md) — skill · 7400 installs
- [memory-discipline](https://affpapa.org/en/nevibecode/skills/memory-discipline.md) — skill · 3900 installs
- [memory-md-management](https://affpapa.org/en/nevibecode/skills/memory-md-management.md) — skill · 3500 installs
- [trader-memory-core](https://affpapa.org/en/nevibecode/skills/trader-memory-core.md) — skill · 3300 installs
- [memory-leak-debugging](https://affpapa.org/en/nevibecode/skills/memory-leak-debugging.md) — skill · 3200 installs

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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