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Memento MCP Server

@veerps57

Repository

Basic information

Category

AI & Agents

Transports

stdio

Author

veerps57

Submitted by

Raghuveer

About Memento MCP Server

Memento is a local-first, LLM-agnostic memory layer. It runs an MCP server over a single SQLite file on your machine, so any MCP-capable AI assistant — Claude Desktop, Claude Code, Cursor, GitHub Copilot, Cline, OpenCode, Aider, a custom agent — can read and write durable, struct

#memory#ai-memory#sqlite#embeddings#local-first

Memento MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "memento": {
      "command": "npx",
      "args": [
        "-y",
        "@psraghuveer/memento",
        "serve"
      ]
    }
  }
}

Memento MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

Fetch the live tool list by running this server in a temporary sandbox using the button above.

Overview

What is Memento?

Memento is a local-first, LLM-agnostic memory layer for AI assistants. It runs an MCP server over a local SQLite file, enabling any MCP-capable AI assistant — Claude Desktop, Claude Code, Cursor, GitHub Copilot, Cline, OpenCode, Aider, and others — to read and write durable, structured memory about you, your work, and your decisions. It is fully offline by default with no outbound network calls and no vendor lock-in.

How to use Memento?

Install and initialize with npx @psraghuveer/memento init, which creates the database, runs migrations, and offers interactive setup. Then paste the printed MCP snippet into your AI client’s configuration and restart the client. After that, ensure the persona snippet reaches the assistant (auto-installed for many file-based clients; manual pasting for UI‑only clients). Verify setup with npx @psraghuveer/memento verify-setup. You can also run the server directly with npx @psraghuveer/memento serve.

Key features of Memento

  • Five typed memory kinds: fact, preference, decision, todo, snippet
  • Vector retrieval with FTS (first‑time model download ~110 MB)
  • Bundled skills and persona snippets for assistant instruction
  • Curated memory packs for seeding conventions and guides
  • Local‑only dashboard web UI (npx @psraghuveer/memento dashboard)

Use cases of Memento

  • Remember user preferences (e.g., preferred package manager) across fresh sessions
  • Recall past decisions without re‑explaining rationale
  • Seed a new project with conventions via starter packs (engineering‑simplicity, pragmatic‑programmer, etc.)
  • Share curated memory packs with a team or across machines

Frequently asked questions

1

What are the runtime requirements for Memento?

Node.js ≥ 22.11 and a C/C++ toolchain (Xcode command‑line tools on macOS, `build-essential` on Debian/Ubuntu) for compiling `better-sqlite3`.

2

Where does Memento store its database?

By default in `$XDG_DATA_HOME/memento/memento.db` (typically `~/.local/share/memento/memento.db` on POSIX). Override with `--db` or the `MEMENTO_DB` environment variable.

3

Does Memento send data over the network?

No outbound network calls by default. The only optional download is the vector‑embedding model (~110 MB) cached locally after the first search.

4

Which AI assistants work with Memento?

Any MCP‑capable client, including Claude Desktop, Claude Code, Cursor, GitHub Copilot, Cline, OpenCode, Aider, VS Code Agent mode, and others.

5

How does Memento handle memory conflicts?

Conflict management is documented in [docs/guides/conflicts.md](docs/guides/conflicts.md). Memento provides workflows for triaging and resolving conflicting memories.

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