Project Atlantis
@ProjectAtlantis-dev
About Project Atlantis
A configurable MCP client/server
Basic information
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"atlantis-mcp-server": {
"command": "python",
"args": [
"server.py",
"\\"
]
}
}
}Tools
No tools detected
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Overview
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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