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Project Atlantis MCP Server

@ProjectAtlantis-dev

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基本信息

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ProjectAtlantis-dev

关于 Project Atlantis MCP Server

A configurable MCP client/server

Project Atlantis MCP Server 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",
        "\\"
      ]
    }
  }
}

Project Atlantis MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

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

常见问题

1

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.

2

What are the runtime requirements?

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

3

How does authentication work?

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

4

Where do custom functions live?

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

5

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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