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Memory MCP 1file

@pomazanbohdan

リポジトリ

基本情報

カテゴリ

メモリとナレッジ

トランスポート

stdio

作者

pomazanbohdan

投稿者

Богдан Помазан

Memory MCP 1file について

A high-performance, pure Rust Model Context Protocol (MCP) server that provides persistent, semantic, and graph-based memory for AI agents.

#vector-search#knowledge-graph#code-indexing

Memory MCP 1file の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "memory": {
      "command": "docker",
      "args": [
        "run",
        "--init",
        "-i",
        "--rm",
        "-v",
        "mcp-data:/data",
        "-v",
        "/absolute/path/to/your/project:/project:ro",
        "ghcr.io/pomazanbohdan/memory-mcp-1file:latest"
      ]
    }
  }
}

Memory MCP 1file のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is Memory Mcp 1file?

Memory Mcp 1file is a high‑performance, pure Rust Model Context Protocol (MCP) server that provides persistent, semantic, and graph‑based memory for AI agents. It is a single, self‑contained executable with no external database, no Python dependencies, no API keys, and requires zero setup—just run a Docker container or binary.

How to use Memory Mcp 1file?

Run the Docker container or the compiled binary. No configuration keys are mentioned in the README; the server starts with built‑in vector search (FastEmbed), a knowledge graph (PetGraph), code indexing, and hybrid retrieval.

Key features of Memory Mcp 1file

  • Embeds SurrealDB for persistent storage
  • Vector search (FastEmbed) for semantic similarity
  • Knowledge graph (PetGraph) for entity relationships
  • Code indexing to understand a codebase
  • Hybrid retrieval via Reciprocal Rank Fusion
  • All models run locally on CPU, no API keys required

Use cases of Memory Mcp 1file

  • AI agents that need persistent, semantic memory across sessions
  • Searching codebases by meaning, not just keywords
  • Storing and retrieving entity relationships in a knowledge graph
  • Offline‑first memory without internet or cloud dependencies

よくある質問

1

What dependencies does Memory Mcp 1file require?

None. It is self‑contained: no Python, no external database, and no API keys. All embedding models run via an embedded ONNX runtime on CPU.

2

Does Memory Mcp 1file need an internet connection?

No. All models run locally on CPU, so no online API calls are made.

3

How is data stored?

Data is persisted using an embedded SurrealDB instance inside the single executable.

4

What transports or protocols does Memory Mcp 1file use?

It implements the Model Context Protocol (MCP); no other transport details are provided in the README.

コメント

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