Comment installer Qdrant MCP ?

Copiez sur cette page la configuration stdio pour Cursor, Claude Desktop, Claude Code ou VS Code. Elle utilise l'installation de l'éditeur, pas un proxy PlugMCP.

Qdrant MCP nécessite-t-il une clé API ?

L'éditeur indique ces variables d'environnement : QDRANT_URL, QDRANT_API_KEY, QDRANT_LOCAL_PATH, QDRANT_MCP_TOOLSETS, QDRANT_MCP_READ_ONLY, QDRANT_MCP_MAX_LIMIT, QDRANT_MCP_SNAPSHOT_ALLOWED_ORIGINS, FASTEMBED_CACHE_PATH.

Quel transport Qdrant MCP utilise-t-il ?

Qdrant MCP s'exécute en local via stdio.

Quand Qdrant MCP a-t-il été vérifié pour la dernière fois ?

Dernière vérification : 2026-11-12. The full Qdrant API as 58 MCP tools: plain-text semantic/BM25/hybrid search and a search advisor.

Serveur MCP Qdrant MCP

Alimenter votre agent

Ajouter ce serveur

La commande propre à l'éditeur. Ce n'est pas un endpoint PlugMCP.

Ajouter à Cursor Ajouter à VS Code Exécuter sur PlugMCP

Host a copy with our keys and logs.

Commande locale

uvx mcp-qdrant==2.12.0

Identifiants fournis par l'éditeur

QDRANT_URL — Qdrant server URL, e.g. http://localhost:6333 (mutually exclusive with QDRANT_LOCAL_PATH)
QDRANT_API_KEY — Qdrant API key, if your instance requires one
QDRANT_LOCAL_PATH — Path to an embedded Qdrant instance, instead of a URL
QDRANT_MCP_TOOLSETS — Comma-separated toolsets to enable: core, search, payload, admin, snapshots, observability
QDRANT_MCP_READ_ONLY — Remove every tool not marked read-only from the registry
QDRANT_MCP_MAX_LIMIT — Largest number of points one tool call may ask for (minimum 30); bigger requests are refused, not cut
QDRANT_MCP_SNAPSHOT_ALLOWED_ORIGINS — Comma-separated http(s) origins qdrant_snapshot_recover may restore from, besides file:// and QDRANT_URL's own origin
FASTEMBED_CACHE_PATH — Where text-embedding models are cached (semantic search needs the mcp-qdrant[embeddings] extra)

Claude Code n'a pas de lien d'installation pour une commande locale. Copiez la commande ci-dessous et exécutez-la dans un terminal.

shClaude Code

1QDRANT_URL=<value> QDRANT_API_KEY=<secret> QDRANT_LOCAL_PATH=<value> QDRANT_MCP_TOOLSETS=<value> QDRANT_MCP_READ_ONLY=<value> QDRANT_MCP_MAX_LIMIT=<value> QDRANT_MCP_SNAPSHOT_ALLOWED_ORIGINS=<value> FASTEMBED_CACHE_PATH=<value> claude mcp add io.github.avaazquezz-mcp-qdrant -- uvx mcp-qdrant==2.12.0

À exécuter dans un terminal.

jsonClaude Desktop

1{2  "mcpServers": {3    "io.github.avaazquezz-mcp-qdrant": {4      "command": "uvx",5      "args": [6        "mcp-qdrant==2.12.0"7      ],8      "env": {9        "QDRANT_URL": "<value>",10        "QDRANT_API_KEY": "<secret>",11        "QDRANT_LOCAL_PATH": "<value>",12        "QDRANT_MCP_TOOLSETS": "<value>",13        "QDRANT_MCP_READ_ONLY": "<value>",14        "QDRANT_MCP_MAX_LIMIT": "<value>",15        "QDRANT_MCP_SNAPSHOT_ALLOWED_ORIGINS": "<value>",16        "FASTEMBED_CACHE_PATH": "<value>"17      }18    }19  }20}

claude_desktop_config.json

Local · pypiInstallation de l'éditeurPas à pas : ajoutez-le dans Claude

URL distante ou commande sur votre machine ? Ce qui distingue les deux installations

Exécuter sur PlugMCP

Host a copy with our keys and logs.

A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.

Lancer

Infos sur le serveur

Local

Transport: stdio

De l'éditeur

Documentation

Qdrant MCP

A Model Context Protocol (MCP) server that exposes the full vector database API as tools — collection management, advanced hybrid search, payload and vector editing, snapshots, and server observability. Not just /.

Variable	Default	Required	Purpose
`QDRANT_URL`	—	No¹	URL of your Qdrant instance, e.g. `http://localhost:6333` or a Qdrant Cloud URL.
`QDRANT_API_KEY`	—	No	API key for `QDRANT_URL`, if your instance requires one.
`QDRANT_LOCAL_PATH`	—	No¹	Path to an embedded/on-disk Qdrant instance, instead of a URL.
`QDRANT_MCP_READ_ONLY`	`false`	No	Removes every tool not marked read-only from the registry. See Read-Only Mode.
`QDRANT_MCP_TRANSPORT`	`stdio`	No	`stdio` (local, for Claude Desktop/Code) or `streamable-http` (network).
`QDRANT_MCP_TOOLSETS`	`core`	No	Comma-separated list of toolsets to register. See Available Tools.
`QDRANT_MCP_SHARED_SECRET`	—	Yes, for `streamable-http`	Bearer token clients must send in the `Authorization` header.
`QDRANT_MCP_HTTP_HOST`	`127.0.0.1`	No	Bind host for `streamable-http`. Use `0.0.0.0` in a container.
`QDRANT_MCP_HTTP_PORT`	`8000`	No	Bind port for `streamable-http`.
`QDRANT_MCP_MAX_LIMIT`	`1000`	No	Largest number of points one tool call may ask for (minimum 30, so every tool's default request fits) (`limit`, groups' `limit × group_size`, a batch's total, the number of ids, ...). A bigger request is refused with a message saying to page, not silently cut.

Tool	Toolset	Read-only	Destructive	Idempotent	Description
`qdrant_health_check`	`core`	✅	❌	✅	Confirm the configured Qdrant instance is reachable and responding.
`qdrant_collection_create`	`core`	❌	❌	❌	Create a collection: either a single unnamed vector (`vector_size` + `distance`), or one or more named vectors (`vectors`, each a full `VectorParams` — size, distance, and optionally its own `multivector_config` for ColBERT-style multi-vectors or `quantization_config`) — exactly one of the two.
`qdrant_collection_list`	`core`	✅	❌	✅	List every collection name in the configured Qdrant instance.
`qdrant_collection_info`	`core`	✅	❌	✅	Return full config and status of one collection.
`qdrant_collection_update`	`core`	❌	❌	✅	Update optimizer/HNSW/collection/vector params on an existing collection.
`qdrant_collection_delete`	`core`	❌	✅	✅	Delete a collection and all its points; a no-op if it doesn't exist.
`qdrant_collection_exists`	`core`	✅	❌	✅	Check whether a collection exists, without raising if it doesn't.
`qdrant_points_upsert`	`core`	❌	✅	✅	Insert or replace points (id + vector + payload) in a collection.
`qdrant_points_get`	`core`	✅	❌	✅	Retrieve points by id; unknown ids are simply omitted, not an error.
`qdrant_points_delete`	`core`	❌	✅	✅	Delete points by id list or by payload filter — exactly one of the two.
`qdrant_points_scroll`	`core`	✅	❌	✅	Page through all points in a collection, optionally filtered.
`qdrant_points_count`	`core`	✅	❌	✅	Count points in a collection, optionally matching a filter.
`qdrant_query`	`core`	✅	❌	✅	Search a collection with Qdrant's unified Query API: vector similarity, hybrid fusion, multi-stage reranking, MMR diversity, payload-based score formulas, ordering by a payload field, or random sampling.
`qdrant_query_batch`	`search`	✅	❌	✅	Run multiple independent queries against one collection in a single round trip — each item takes every query mode and tuning parameter of `qdrant_query` (plain vector, fusion over prefetch, MMR, formula, order_by, sample, search_params, score_threshold, offset); `timeout_seconds` and `consistency` apply to the whole batch.
`qdrant_query_groups`	`search`	✅	❌	✅	Vector query grouped by a payload field, up to `group_size` hits per group — e.g. the best-matching chunks per source document.
`qdrant_recommend`	`search`	✅	❌	✅	Find points similar to a set of positive examples and dissimilar to a set of negative ones (vectors or point ids) — Qdrant's recommendation API.
`qdrant_recommend_batch`	`search`	✅	❌	✅	Run multiple independent recommend queries against one collection in a single round trip.
`qdrant_recommend_groups`	`search`	✅	❌	✅	Recommend query grouped by a payload field, up to `group_size` hits per group.
`qdrant_discover`	`search`	✅	❌	✅	Rank points by how well they fit a target within positive/negative context pairs (vectors or point ids) — Qdrant's discovery search, a finer-grained alternative to recommend.
`qdrant_discover_batch`	`search`	✅	❌	✅	Run multiple independent discover queries against one collection in a single round trip.
`qdrant_distance_matrix_pairs`	`search`	✅	❌	✅	Pairwise distance matrix between a random sample of points: for each of `sample` points, its `limit` closest neighbors among that same sample — returned as a flat list of (a, b, score) pairs.
`qdrant_distance_matrix_offsets`	`search`	✅	❌	✅	Same distance matrix as `qdrant_distance_matrix_pairs`, in a column-oriented shape (offsets into a shared id list + a parallel score array) — more compact for large samples.
`qdrant_payload_set`	`payload`	❌	❌	✅	Merge fields into the payload of selected points — exactly one of `ids`/`points_filter`.
`qdrant_payload_overwrite`	`payload`	❌	✅	✅	Replace the entire payload of selected points with `payload` — exactly one of `ids`/`points_filter`.
`qdrant_payload_delete`	`payload`	❌	✅	✅	Delete specific payload keys from selected points — exactly one of `ids`/`points_filter`.
`qdrant_payload_clear`	`payload`	❌	✅	✅	Wipe the entire payload of selected points, keeping their vectors — exactly one of `ids`/`points_filter`.
`qdrant_payload_facet`	`payload`	✅	❌	✅	Count distinct values of a payload field across the collection (or a filtered subset) — e.g. how many points per `city`.
`qdrant_payload_index_create`	`payload`	❌	❌	✅	Create a payload index on `field_name`, speeding up filters that use it.
`qdrant_payload_index_delete`	`payload`	❌	✅	✅	Delete the payload index on `field_name`.
`qdrant_collection_vector_create`	`payload`	❌	❌	✅	Add a new named vector (dense or sparse) to a collection that already has points, without touching them.
`qdrant_collection_vector_delete`	`payload`	❌	✅	✅	Remove a named vector (dense or sparse) from a collection — points keep their other vectors and payload.
`qdrant_points_batch_update`	`payload`	❌	✅	❌	Run multiple point operations (upsert, delete, set/overwrite/delete/clear payload, update/delete vectors) against one collection, in the order given, in a single request.
`qdrant_vectors_update`	`payload`	❌	✅	✅	Replace the vector(s) of existing points by id — leaves their payload untouched.
`qdrant_vectors_delete`	`payload`	❌	✅	✅	Remove specific named vectors from selected points, keeping their payload and other vectors — exactly one of `ids`/`points_filter`.
`qdrant_alias_list`	`admin`	✅	❌	✅	List every alias on the server with the collection it points to.
`qdrant_collection_aliases`	`admin`	✅	❌	✅	List the aliases that point to one collection (an empty list if it has none).
`qdrant_alias_update`	`admin`	❌	✅	❌	Create, rename, re-point or delete aliases — the basis of a zero-downtime reindex: build the new collection, then switch the alias that clients use.
`qdrant_collection_cluster_info`	`admin`	✅	❌	✅	Shard layout of a collection: how many shards it has and, for each local shard, its point count and replica state.
`qdrant_collection_optimizations`	`admin`	✅	❌	✅	Progress of the background optimizer for a collection — answers "has it finished indexing?" and "why isn't the collection green?".
`qdrant_collection_copy`	`admin`	❌	✅	✅	Copy points (all vectors — dense, sparse and multivector — and payload) from one collection to another of the same Qdrant instance, entirely server-side: the vectors never pass through the model.
`qdrant_payload_schema_infer`	`admin`	✅	❌	✅	Profile the payload keys that actually occur in a collection, so filters can be written against real keys instead of guessed ones.
`qdrant_snapshot_create`	`snapshots`	❌	❌	❌	Create a snapshot of one collection's current state.
`qdrant_snapshot_list`	`snapshots`	✅	❌	✅	List the snapshots stored for one collection.
`qdrant_snapshot_delete`	`snapshots`	❌	✅	✅	Delete a collection snapshot, freeing its disk space on the server — does not touch the live collection.
`qdrant_snapshot_recover`	`snapshots`	❌	✅	✅	Overwrite `collection_name` with the state captured in a snapshot — everything written since that snapshot is lost.
`qdrant_snapshot_download`	`snapshots`	✅	❌	✅	Confirm a collection snapshot exists and return where to fetch it from — this tool does not transfer the (potentially huge) snapshot file itself; download it yourself (e.g. `curl`) from the returned `url`.
`qdrant_storage_snapshot_create`	`snapshots`	❌	❌	❌	Create a snapshot of the whole storage (every collection and server config), not just one collection.
`qdrant_storage_snapshot_list`	`snapshots`	✅	❌	✅	List the full-storage snapshots stored on the server.
`qdrant_storage_snapshot_delete`	`snapshots`	❌	✅	✅	Delete a full-storage snapshot, freeing its disk space.
`qdrant_storage_snapshot_download`	`snapshots`	✅	❌	✅	Confirm a full-storage snapshot exists and return where to fetch it from — same caveat as `qdrant_snapshot_download`: this tool does not transfer the file itself.
`qdrant_telemetry`	`observability`	✅	❌	✅	Server-wide telemetry: build info, per-collection stats, request counters, memory and hardware usage.
`qdrant_metrics_prometheus`	`observability`	✅	❌	✅	Return the URL where Qdrant serves Prometheus-format metrics — this tool does not fetch the metrics themselves (they're plain text, not JSON); point your Prometheus scraper at the returned `url` instead.
`qdrant_quotas_get`	`observability`	✅	❌	✅	Current server-wide resource quotas (memory/disk limits) and actual usage.
`qdrant_quotas_set`	`observability`	❌	❌	✅	Update server-wide resource quotas.
`qdrant_issues_list`	`observability`	✅	❌	✅	List the issues Qdrant has detected about its own configuration (e.g. a heavily-filtered field with no payload index).
`qdrant_issues_clear`	`observability`	❌	✅	✅	Clear all accumulated issues.

Tool

Toolset

Read-only

Destructive

Idempotent

Description

qdrant_health_check

core

✅

❌

✅

Confirm the configured Qdrant instance is reachable and responding.

qdrant_collection_create

core

❌

Create a collection: either a single unnamed vector (vector_size + distance), or one or more named vectors (vectors, each a full VectorParams — size, distance, and optionally its own multivector_config for ColBERT-style multi-vectors or quantization_config) — exactly one of the two.

qdrant_collection_list

core

✅

❌

✅

List every collection name in the configured Qdrant instance.

qdrant_collection_info

core

✅

❌

✅

Return full config and status of one collection.

qdrant_collection_update

core

❌

✅

Update optimizer/HNSW/collection/vector params on an existing collection.

qdrant_collection_delete

core

❌

✅

Delete a collection and all its points; a no-op if it doesn't exist.

qdrant_collection_exists

core

✅

❌

✅

Check whether a collection exists, without raising if it doesn't.

qdrant_points_upsert

core

❌

✅

Insert or replace points (id + vector + payload) in a collection.

qdrant_points_get

core

✅

❌

✅

Retrieve points by id; unknown ids are simply omitted, not an error.

qdrant_points_delete

core

❌

✅

Delete points by id list or by payload filter — exactly one of the two.

qdrant_points_scroll

core

✅

❌

✅

Page through all points in a collection, optionally filtered.

qdrant_points_count

core

✅

❌

✅

Count points in a collection, optionally matching a filter.

qdrant_query

core

✅

❌

✅

Search a collection with Qdrant's unified Query API: vector similarity, hybrid fusion, multi-stage reranking, MMR diversity, payload-based score formulas, ordering by a payload field, or random sampling.

qdrant_query_batch

search

✅

❌

✅

Run multiple independent queries against one collection in a single round trip — each item takes every query mode and tuning parameter of qdrant_query (plain vector, fusion over prefetch, MMR, formula, order_by, sample, search_params, score_threshold, offset); timeout_seconds and consistency apply to the whole batch.

qdrant_query_groups

search

✅

❌

✅

Vector query grouped by a payload field, up to group_size hits per group — e.g. the best-matching chunks per source document.

qdrant_recommend

search

✅

❌

✅

Find points similar to a set of positive examples and dissimilar to a set of negative ones (vectors or point ids) — Qdrant's recommendation API.

qdrant_recommend_batch

search

✅

❌

✅

Run multiple independent recommend queries against one collection in a single round trip.

qdrant_recommend_groups

search

✅

❌

✅

Recommend query grouped by a payload field, up to group_size hits per group.

qdrant_discover

search

✅

❌

✅

Rank points by how well they fit a target within positive/negative context pairs (vectors or point ids) — Qdrant's discovery search, a finer-grained alternative to recommend.

qdrant_discover_batch

search

✅

❌

✅

Run multiple independent discover queries against one collection in a single round trip.

qdrant_distance_matrix_pairs

search

✅

❌

✅

Pairwise distance matrix between a random sample of points: for each of sample points, its limit closest neighbors among that same sample — returned as a flat list of (a, b, score) pairs.

qdrant_distance_matrix_offsets

search

✅

❌

✅

Same distance matrix as qdrant_distance_matrix_pairs, in a column-oriented shape (offsets into a shared id list + a parallel score array) — more compact for large samples.

qdrant_payload_set

payload

❌

✅

Merge fields into the payload of selected points — exactly one of ids/points_filter.

qdrant_payload_overwrite

payload

❌

✅

Replace the entire payload of selected points with payload — exactly one of ids/points_filter.

qdrant_payload_delete

payload

❌

✅

Delete specific payload keys from selected points — exactly one of ids/points_filter.

qdrant_payload_clear

payload

❌

✅

Wipe the entire payload of selected points, keeping their vectors — exactly one of ids/points_filter.

qdrant_payload_facet

payload

✅

❌

✅

Count distinct values of a payload field across the collection (or a filtered subset) — e.g. how many points per city.

qdrant_payload_index_create

payload

❌

✅

Create a payload index on field_name, speeding up filters that use it.

qdrant_payload_index_delete

payload

❌

✅

Delete the payload index on field_name.

qdrant_collection_vector_create

payload

❌

✅

Add a new named vector (dense or sparse) to a collection that already has points, without touching them.

qdrant_collection_vector_delete

payload

❌

✅

Remove a named vector (dense or sparse) from a collection — points keep their other vectors and payload.

qdrant_points_batch_update

payload

❌

✅

❌

Run multiple point operations (upsert, delete, set/overwrite/delete/clear payload, update/delete vectors) against one collection, in the order given, in a single request.

qdrant_vectors_update

payload

❌

✅

Replace the vector(s) of existing points by id — leaves their payload untouched.

qdrant_vectors_delete

payload

❌

✅

Remove specific named vectors from selected points, keeping their payload and other vectors — exactly one of ids/points_filter.

qdrant_alias_list

admin

✅

❌

✅

List every alias on the server with the collection it points to.

qdrant_collection_aliases

admin

✅

❌

✅

List the aliases that point to one collection (an empty list if it has none).

qdrant_alias_update

admin

❌

✅

❌

Create, rename, re-point or delete aliases — the basis of a zero-downtime reindex: build the new collection, then switch the alias that clients use.

qdrant_collection_cluster_info

admin

✅

❌

✅

Shard layout of a collection: how many shards it has and, for each local shard, its point count and replica state.

qdrant_collection_optimizations

admin

✅

❌

✅

Progress of the background optimizer for a collection — answers "has it finished indexing?" and "why isn't the collection green?".

qdrant_collection_copy

admin

❌

✅

Copy points (all vectors — dense, sparse and multivector — and payload) from one collection to another of the same Qdrant instance, entirely server-side: the vectors never pass through the model.

qdrant_payload_schema_infer

admin

✅

❌

✅

Profile the payload keys that actually occur in a collection, so filters can be written against real keys instead of guessed ones.

qdrant_snapshot_create

snapshots

❌

Create a snapshot of one collection's current state.

qdrant_snapshot_list

snapshots

✅

❌

✅

List the snapshots stored for one collection.

qdrant_snapshot_delete

snapshots

❌

✅

Delete a collection snapshot, freeing its disk space on the server — does not touch the live collection.

qdrant_snapshot_recover

snapshots

❌

✅

Overwrite collection_name with the state captured in a snapshot — everything written since that snapshot is lost.

qdrant_snapshot_download

snapshots

✅

❌

✅

Confirm a collection snapshot exists and return where to fetch it from — this tool does not transfer the (potentially huge) snapshot file itself; download it yourself (e.g. curl) from the returned url.

qdrant_storage_snapshot_create

snapshots

❌

Create a snapshot of the whole storage (every collection and server config), not just one collection.

qdrant_storage_snapshot_list

snapshots

✅

❌

✅

List the full-storage snapshots stored on the server.

qdrant_storage_snapshot_delete

snapshots

❌

✅

Delete a full-storage snapshot, freeing its disk space.

qdrant_storage_snapshot_download

snapshots

✅

❌

✅

Confirm a full-storage snapshot exists and return where to fetch it from — same caveat as qdrant_snapshot_download: this tool does not transfer the file itself.

qdrant_telemetry

observability

✅

❌

✅

Server-wide telemetry: build info, per-collection stats, request counters, memory and hardware usage.

qdrant_metrics_prometheus

observability

✅

❌

✅

Return the URL where Qdrant serves Prometheus-format metrics — this tool does not fetch the metrics themselves (they're plain text, not JSON); point your Prometheus scraper at the returned url instead.

qdrant_quotas_get

observability

✅

❌

✅

Current server-wide resource quotas (memory/disk limits) and actual usage.

qdrant_quotas_set

observability

❌

✅

Update server-wide resource quotas.

qdrant_issues_list

observability

✅

❌

✅

List the issues Qdrant has detected about its own configuration (e.g. a heavily-filtered field with no payload index).

qdrant_issues_clear

observability

❌

✅

Clear all accumulated issues.

Ajouter ce serveur

Host a copy with our keys and logs.

Infos sur le serveur

Documentation

Qdrant MCP

Table of Contents

Overview

Key Features

Requirements

Installation

PyPI

Docker

Claude Desktop bundle (`.mcpb`)

Quick Start

Connecting to Claude

Claude Desktop / Claude Code (local, `stdio`)

Remote (`streamable-http`)

Configuration Reference

Available Tools

Read-Only Mode

Architecture

Security

Development

Versioning & Changelog

License

Qdrant MCP

Outils

Questions

Comment installer Qdrant MCP ?

Qdrant MCP nécessite-t-il une clé API ?

Quel transport Qdrant MCP utilise-t-il ?

Quand Qdrant MCP a-t-il été vérifié pour la dernière fois ?

Ajouter ce serveur

Host a copy with our keys and logs.

Infos sur le serveur

Documentation

Qdrant MCP

Table of Contents

Overview

Key Features

Requirements

Installation

PyPI

Docker

Claude Desktop bundle (.mcpb)

Quick Start

Connecting to Claude

Claude Desktop / Claude Code (local, stdio)

Remote (streamable-http)

Configuration Reference

Available Tools

Read-Only Mode

Architecture

Security

Development

Versioning & Changelog

License

Outils

Questions

Comment installer Qdrant MCP ?

Qdrant MCP nécessite-t-il une clé API ?

Quel transport Qdrant MCP utilise-t-il ?

Quand Qdrant MCP a-t-il été vérifié pour la dernière fois ?

Claude Desktop bundle (`.mcpb`)

Claude Desktop / Claude Code (local, `stdio`)

Remote (`streamable-http`)