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Memory MCP 1file

@pomazanbohdan

Repository

Basic information

Category

Memory & Knowledge

Transports

stdio

Author

pomazanbohdan

Submitted by

Богдан Помазан

About Memory MCP 1file

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 config

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

{
  "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 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.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

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

Frequently asked questions

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.

Comments

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