Mnemo MCP runs on your own machine — the client starts it, so there is no endpoint to ping. 3 037 installs a week from pypi. Last commit 17 Sep 2026.
Persistent AI memory with hybrid search and embedded sync. Open, free, unlimited.
Today is the operative word: we check Mnemo MCP 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 mnemo-mcp -- uvx mnemo-mcp
{
"mcpServers": {
"mnemo-mcp": {
"args": [
"mnemo-mcp"
],
"command": "uvx"
}
}
}
[mcp_servers.mnemo-mcp]
command = "uvx"
args = ["mnemo-mcp"]
{
"mcpServers": {
"mnemo-mcp": {
"args": [
"mnemo-mcp"
],
"command": "uvx"
}
}
}
{
"mcpServers": {
"mnemo-mcp": {
"args": [
"mnemo-mcp"
],
"command": "uvx"
}
}
}
This one needs environment variables set before it will start:
API_KEYS (Provider API keys (format: PROVIDER_API_KEY:key,...). Select models per task with EMBEDDING_MODELS / RERANK_MODELS / LLM_MODELS (CSV provider/model, order = litellm fallback); provider is inferred from the model prefix. Empty embedding/rerank chains select Fastretrieval local ONNX/GGUF models; configured cloud chains never silently fall back to local.).
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.