Basically we have a distributed linux-style system that provides tool infra for bots. Tools are arranged in folders for easy management across
Most team communication work still happens through a UI a human drives. Atlantis MCP server moves it into the conversation instead. Basically we have a distributed linux-style system that provides tool infra for bots. Tools are arranged in folders for easy management across functions and teams. Teams can call each other's functions directly or of course the bots can.
The server publishes 5 tools. What each one is for:
Fields — remote_ownerremote_nameapplocationfunctionMulti — user setups**: Specify owner and remote in shared environmentsArchitecture — Caveat: MCP terminology is already terrible and calling things 'servers' or 'hosts' just makes it more confusing because MCP is inherently p2pDirectories — 1. Python Remote (MCP P2P server) (python-server/) - Location of our 'remote'. Runs locally but can be controlled remotelyTroubleshooting — If MCP tools aren't working (e.g. returning Unknown tool errors), check the server log first. The Python server writes detailed logs toConfiguration is passed through the environment: OPENROUTER_API_KEY, ANTHROPIC_API_KEY, OPENWEATHER_API_KEY. Treat anything key-shaped as a real credential — scope it to the minimum the server needs, and rotate it if it ever lands in a shared config.
The server ships on npm as since, so your MCP client can launch it on demand — there is no separate build step. Add the server block to your client's configuration, restart it, and the tools register themselves.
This sits in the team communication group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. Atlantis's toolset — Fields, Multi, Architecture and 2 more — is a fair guide to whether it matches your workflow. It is maintained by ProjectAtlantis-dev; worth a glance at recent repository activity before you build anything load-bearing on it.
We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.
| Tool | What it does |
|---|---|
| Fields | remote_owner*remote_name*app*location*function |
| Multi | user setups**: Specify owner and remote in shared environments |
| Architecture | Caveat: MCP terminology is already terrible and calling things 'servers' or 'hosts' just makes it more confusing because MCP is inherently p2p |
| Directories | 1. **Python Remote (MCP P2P server)** (python-server/) - Location of our 'remote'. Runs locally but can be controlled remotely |
| Troubleshooting | If MCP tools aren't working (e.g. returning Unknown tool errors), **check the server log first**. The Python server writes detailed logs to **python-server/runServer.log** — this file shows exactly what's happening with |
{
"mcpServers": {
"atlantis": {
"command": "npx",
"args": ["-y", "since"],
"env": {
"OPENROUTER_API_KEY": "your-value",
"ANTHROPIC_API_KEY": "your-value",
"OPENWEATHER_API_KEY": "your-value"
}
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
| Variable | Description | Required |
|---|---|---|
| OPENROUTER_API_KEY | Credential the server authenticates with. | Yes |
| ANTHROPIC_API_KEY | Credential the server authenticates with. | Yes |
| OPENWEATHER_API_KEY | Credential the server authenticates with. | Yes |
Your assistant inside the workspace — read channels, search history, post messages and tame the noise.
Inbox intelligence — search, read, draft and send Gmail through your assistant with OAuth auto-setup.
Read and write Jira, Confluence, Bitbucket, JSM and Compass from your AI client — with your own permissions.
Read and send Telegram messages through your assistant — chats, channels and history via the client API.
Enables Discord bot integration with Model Context Protocol (MCP) compatible applications like Claude Desktop.
Exposes REST APIs defined by OpenAPI specifications as Model Context Protocol (MCP) tools, facilitating seamless integration into MCP-based workflows.