Vector Memory runs on your own machine — the client starts it, so there is no endpoint to ping. 205 installs a week from pypi.
Semantic document memory using Redis vector store. Save and recall files with natural language.
Today is the operative word: we check Vector Memory 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 vector-memory -- uvx mcp-server-vector-memory
{
"mcpServers": {
"vector-memory": {
"args": [
"mcp-server-vector-memory"
],
"command": "uvx"
}
}
}
[mcp_servers.vector-memory]
command = "uvx"
args = ["mcp-server-vector-memory"]
{
"mcpServers": {
"vector-memory": {
"args": [
"mcp-server-vector-memory"
],
"command": "uvx"
}
}
}
{
"mcpServers": {
"vector-memory": {
"args": [
"mcp-server-vector-memory"
],
"command": "uvx"
}
}
}
Local FAISS vector database for RAG with document ingestion, semantic search, and MCP prompts.
Persistent semantic memory for AI agents using local ChromaDB vector search. No cloud required.
Shared cross-LLM long-term memory over MCP: semantic recall, sessions, and media (pgvector).
Bilingual dual memory with SSC for AI agents. Semantic search, embeddings, profiles.
Portable agent memory anchored on Solana. Local SQLite + vector recall, open export.
RAG memory for LLM agents over Garnet Vector Sets: store text as embeddings, recall by meaning.
Graph + vector memory for agents: recall, ingest, search, distill. Local or remote backend.
Local-first image, vector and document toolkit that measures its own output. Nothing uploaded.
Answers built from our own checks of this server.