Needs file `plugins/anythingllm_mcp_servers.json` following the [MCP Server Specification](https://github.com/modelcontextprotocol/servers?tab=readme-
Needs file plugins/anythingllm_mcp_servers.json following the MCP Server Specification: ```json { "mcpServers": { "exoscale": { "command": "uv". That is what the exoscale mcp mcp server brings to an AI assistant: the same capability, reachable through the Model Context Protocol rather than a separate app or dashboard.
Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client. The configuration blocks on this page cover the common clients.
Configuration is passed through the environment: EXO_KEY_NAME, EXO_KEY_SECRET. 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.
This sits in the file and storage access group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. It is maintained by czephyr; 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We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.
{
"mcpServers": {
"exoscale": {
"command": "uv",
"args": [
"--directory",
"/app/server/storage/exoscale-mcp-server",
"run",
"exoscale-mcp-server.py"
]
"env": {
"EXO_KEY_NAME": "EXO..."
"EXO_KEY_SECRET": "Eya1...."
}
}
}
}Configuration as documented by the project. Restart the client after saving.
| Variable | Description | Required |
|---|---|---|
| EXO_KEY_NAME | Credential the server authenticates with. | Yes |
| EXO_KEY_SECRET | Credential the server authenticates with. | Yes |
Scoped local file access — read, write, search and reorganise files in directories you explicitly allow.
Search and read your Drive — Docs, Sheets and files become context your assistant can actually use.
Query, modify and analyse local SQLite databases in conversation — the fastest way to chat with a data file.
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Chat with your second brain — search, read and write vault notes through the Local REST API.
Connects AI models to an Obsidian knowledge base for direct access and manipulation of notes and folders.