Skip to main content
Glama

Store MCP Server

A Model Context Protocol (MCP) server that enables AI agents to store and retrieve information persistently.

Project Structure

store_mcp/
├── README.md                 # This file
├── pyproject.toml           # Project dependencies and configuration
├── src/
│   └── store_mcp/
│       ├── __init__.py      # Package initialization
│       ├── server.py        # Main MCP server implementation
│       └── storage.py       # Storage backend (JSON/SQLite)
└── tests/
    ├── __init__.py
    └── test_server.py       # Unit tests

Related MCP server: Memory MCP Server

Features

  • Store Information: Save key-value pairs or structured data

  • Retrieve Information: Query stored data by key or search criteria

  • List Keys: View all available stored keys

  • Delete Information: Remove stored data when no longer needed

  • Persistent Storage: Data persists across sessions

Installation

# Install dependencies
pip install -e .

Usage

# Run the MCP server
python -m store_mcp.server

MCP Tools

The server exposes the following tools to AI agents:

  • store_data: Store information with a key

  • retrieve_data: Retrieve information by key

  • list_keys: List all stored keys

  • delete_data: Delete stored information by key

  • search_data: Search stored information by pattern or content

Configuration

MCP Client Configuration

To use this server with an MCP client (like Claude Desktop), add it to your MCP settings configuration file:

For Claude Desktop on MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json

For Claude Desktop on Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "store": {
      "command": "python",
      "args": [
        "-m",
        "store_mcp.server"
      ],
      "env": {
        "PYTHONPATH": "/absolute/path/to/store_mcp/src"
      }
    }
  }
}

Alternative using uvx (if installed via pip):

{
  "mcpServers": {
    "store": {
      "command": "uvx",
      "args": [
        "--from",
        "/absolute/path/to/store_mcp",
        "python",
        "-m",
        "store_mcp.server"
      ]
    }
  }
}

Storage Configuration

The server uses a local file-based storage system (JSON) located at:

  • Default: ~/.store_mcp/data.json

To use a custom storage location, modify server.py and initialize Storage with a custom path:

storage = Storage("/path/to/custom/data.json")

Environment Variables

You can set the following environment variables:

  • STORE_MCP_PATH: Custom path for the storage file (default: ~/.store_mcp/data.json)

Example configuration with custom storage path:

{
  "mcpServers": {
    "store": {
      "command": "python",
      "args": ["-m", "store_mcp.server"],
      "env": {
        "PYTHONPATH": "/absolute/path/to/store_mcp/src",
        "STORE_MCP_PATH": "/custom/path/to/storage.json"
      }
    }
  }
}

Development

# Run tests
pytest tests/

Requirements

  • Python 3.10+

  • mcp library

F
license - not found
-
quality - not tested
D
maintenance

Maintenance

Maintainers
Response time
Release cycle
Releases (12mo)
Commit activity

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Related MCP Servers

  • A
    license
    -
    quality
    D
    maintenance
    Enables AI assistants to store and retrieve persistent memories with a web management interface. Supports creating, searching, and managing memories through natural language commands or a visual web dashboard.
    22
    1
    MIT
  • A
    license
    -
    quality
    D
    maintenance
    Enables persistent storage and retrieval of user preferences, context, and decisions across AI sessions using a structured JSON-based memory system. It provides tools for storing, searching, updating, and managing memories organized by namespaces and tags.
    13
    MIT
  • A
    license
    -
    quality
    D
    maintenance
    Provides persistent memory storage for AI agents with full-text search, tagging, and importance levels, enabling agents to store and retrieve memories efficiently.
    MIT

View all related MCP servers

Related MCP Connectors

  • Persistent memory for AI agents. Search, store, and recall across sessions.

  • Persistent memory and knowledge management for AI agents with semantic search and 50+ tools.

  • Shared, governed long-term memory for AI agents across tools and sessions via MCP and REST.

View all MCP Connectors

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/mariano-cecowski/store_mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server