Project Atlantis

Name: Project Atlantis
Author: ProjectAtlantis-dev

@ProjectAtlantis-dev

代码仓库

关于 Project Atlantis

A configurable MCP client/server

基本信息

分类

其他

运行时

python

传输方式

stdio

发布者

ProjectAtlantis-dev

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "atlantis-mcp-server": {
      "command": "python",
      "args": [
        "server.py",
        "\\"
      ]
    }
  }
}

工具

未检测到工具

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is Project Atlantis?

Project Atlantis is a Python MCP remote server that lets users install custom functions as tools and manage third‑party MCP servers on the fly. It connects to an experimental cloud server at projectatlantis.ai for tool sharing and authentication, and is designed for developers exploring MCP capabilities.

How to use Project Atlantis?

Install Python 3.12 and Node, then configure the runServer script with your email and API key, and sign in at projectatlantis.ai. Run the Python server process, which will auto-connect to the cloud.

Key features of Project Atlantis

Dynamic functions as hot‑reloaded Python tools
Dynamic MCP server management via JSON config
Cloud‑connected for auth and tool sharing
Supports multiple remote instances
Local MCP client for use with Claude or Cursor

Use cases of Project Atlantis

Experimenting with MCP protocol and remote server concepts
Building custom tools with hot‑reloaded Python functions
Managing and sharing third‑party MCP servers
Running multiple remote instances across machines

FAQ from Project Atlantis

What is the difference between a remote and an MCP server?

The remote is the Python MCP host process, while MCP servers are third‑party tools that can be dynamically installed via JSON config files.

What are the runtime requirements?

Python 3.12 (most stable) and Node for the MCP client, plus uv/uvx and npx for MCP tooling.

How does authentication work?

Authentication is currently handled through the Atlantis cloud at projectatlantis.ai using your email and an API key (default foobar).

Where do custom functions live?

Custom functions are stored in the dynamic_functions/ folder and are automatically loaded on start with hot‑reload support.

What transports does the server support?

The remote uses a WebSocket cloud connection, and a local npx‑based MCP client that does not require the cloud (but only exposes tools on the local box).

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