Memory

Model Context Protocol Servers

javascript

0

GitHub Stars

javascript

Language

7 months ago

First Indexed

3 months ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs

{
  "mcpServers": {
    "jeff-nasseri-servers": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-memory"
      ]
    }
  }
}

You deploy MCP servers to give large language models secure, controlled access to tools and data sources. With MCP, you can expose capabilities as defined endpoints that an AI agent can invoke safely, while keeping your systems protected and auditable.

How to use

You connect an MCP client to the server you run, then invoke the available tools through the client. Start by launching the servers you need, then configure your client to point at those servers. Once connected, your AI agent can access the exposed tools and data sources in a controlled, auditable way. Keep access policies and environment constraints in mind to maintain secure operation.

How to install

Prerequisites you should have before starting: Node.js and npm, Python and pip, and a shell where you can run commands.

Install and run the Memory MCP server (TypeScript) using the following command.

npx -y @modelcontextprotocol/server-memory

Install and run the Git MCP server (Python) using one of these approaches.

# Option 1: run with uvx
uvx mcp-server-git

# Option 2: run with Python after installation
python -m mcp_server_git

Notes and tips

If you plan to use multiple MCP servers together, configure your MCP client with each server’s command path so the client can start and route tool calls appropriately.