Skip to main content
Glama
deenesjakoruzh
Ripnrip

qdrant-mcp-server

by Ripnrip
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

qdrant-mcp-server (maintained fork)

Fork of the abandoned PyPI package qdrant-mcp-server 0.1.0 (author fiyen; upstream github.com/fiyen/qdrant-mcp-server is 404 — no repo exists to PR against).

Why this fork exists

The original eagerly loads a sentence-transformers/all-MiniLM-L6-v2 model in __init__. As a stdio MCP server, every agent runtime/session spawns its own copy, so N idle sessions pin N × ~1.35 GB of duplicated model memory (measured: 5 copies = 5.7 GB). See the generalized "stdio trap" write-up.

Related MCP server: Qdrant MCP Server

Changes vs PyPI 0.1.0

  • Lazy-load patch: the embedding model loads on the first generate_embedding call instead of at startup. Idle copies cost ~30 MB. (lazy-load.patch in the repo root is the diff for reference.)

Install (replaces the PyPI install)

uv tool install --force git+https://github.com/Ripnrip/qdrant-mcp-server

Then the existing MCP configs (command = /Users/admin/.local/bin/qdrant-mcp-server) keep working, and future uv tool upgrade pulls from this fork, not dead PyPI 0.1.0.

After any reinstall, restart running qdrant-mcp-server instances (the Swift reaper LaunchAgent handles orphan cleanup: com.local.qdrant-mcp-reaper).

Context: HAB-354 · ~/Documents/Developer/qdrant-mcp-ram-fix-2026-08-24/

This server cannot be deployed

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Maintenance

ActivityMaintained
ResponsivenessNo issues

Resources

Related MCP Connectors

Related MCP Servers

  • Qdrant MCP Server

    andrewlwn77
    A
    license
    Not graded
    quality
    D
    maintenance
    Provides semantic memory capabilities using Qdrant vector database with configurable embedding providers, allowing storage and retrieval of information using vector similarity.
    16 PyPI
    2
    Apache 2.0

  • Qdrant MCP Server

    mhalder
    A
    license
    Not graded
    quality
    C
    maintenance
    Enables semantic search and document management using a local Qdrant vector database with OpenAI embeddings. Supports natural language queries, metadata filtering, and collection management for AI-powered document retrieval.
    70 npm
    37
    MIT

  • Qdrant MCP Server

    mcandiav
    A
    license
    Not graded
    quality
    D
    maintenance
    Enables storing and retrieving information using semantic search with Qdrant vector database. Acts as a memory layer for LLMs to persistently store and semantically search through information and metadata.
    Apache 2.0