MCP Qdrant runs on your own machine — the client starts it, so there is no endpoint to ping. 50 installs a week from npm.
Read-only Qdrant vector DB for AI agents — collections, info, browse points, count, search.
The linked repository no longer exists on GitHub — it was deleted or made private.
Quiet is not dead — but it is worth knowing when it wakes up, or when someone else takes it over. We watch the repository and tell you either way.
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 mcp-qdrant -- npx -y @infoinlet/mcp-qdrant
{
"mcpServers": {
"mcp-qdrant": {
"command": "npx",
"args": [
"-y",
"@infoinlet/mcp-qdrant"
]
}
}
}
[mcp_servers.mcp-qdrant]
command = "npx"
args = ["-y", "@infoinlet/mcp-qdrant"]
{
"mcpServers": {
"mcp-qdrant": {
"command": "npx",
"args": [
"-y",
"@infoinlet/mcp-qdrant"
]
}
}
}
{
"servers": {
"mcp-qdrant": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@infoinlet/mcp-qdrant"
]
}
}
}
Vector collections and document search backed by a Chroma HTTP service.
MCP server for Oracle, MSSQL, PostgreSQL, MySQL, SQLite, MongoDB, and Qdrant vector search access.
Store and retrieve text in a Qdrant vector database by similarity search.
Astra DB tools for agents: schema, find, vector search, guarded writes, and interactive views.
Persistent semantic memory for AI agents using local ChromaDB vector search. No cloud required.
Graph + vector memory for agents: recall, ingest, search, distill. Local or remote backend.
Memory, reflection and safety for AI agents. Hosted or local, no vector database.
Markdown-first long-term memory for AI agents. Hybrid BM25 + vector search, runs locally.
Answers built from our own checks of this server.