dashAI (unofficial) runs on your own machine — the client starts it, so there is no endpoint to ping. Last commit 15 Sep 2026.
Train, track and query models on a running dashAI instance. Read-oriented, no delete tools.
Today is the operative word: we check dashAI (unofficial) every 15 minutes and re-read its code on every release. Watch it and you find out the day that stops being true.
This server runs on your own machine — install it with the package manager and the client starts it for you. Package name taken from the official registry entry.
claude mcp add dashai-mcp -- uvx dashai-mcp
{
"mcpServers": {
"dashai-mcp": {
"args": [
"dashai-mcp"
],
"command": "uvx"
}
}
}
[mcp_servers.dashai-mcp]
command = "uvx"
args = ["dashai-mcp"]
{
"mcpServers": {
"dashai-mcp": {
"args": [
"dashai-mcp"
],
"command": "uvx"
}
}
}
{
"mcpServers": {
"dashai-mcp": {
"args": [
"dashai-mcp"
],
"command": "uvx"
}
}
}
This one needs environment variables set before it will start:
DASHAI_BASE_URL (URL of the dashAI backend. Defaults to http://localhost:8000.), DASHAI_ALLOW_REMOTE (Set to 1 to allow a non-localhost backend. dashAI's API has no authentication, so pointing this server at a remote host exposes an ML backend with no door on it — read the README before enabling.), DASHAI_TIMEOUT (Seconds to wait per request. Defaults to 30.).
The author declared them in the registry entry; get the values from the project itself.
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Answers built from our own checks of this server.