Quadrant + Konnectify
Quadrant Integration with Konnectify
Automate Qdrant vector database operations through Konnectify. Manage collections, aliases, indexes, shards, clusters, snapshots, points, vectors, payloads, searches, recommendations, and hybrid query workflows.
Vector Database Qdrant API API Key Auth 0 Triggers 34 Actions
What is Quadrant?
Quadrant is implemented as a Qdrant API connector for vector database administration and search workflows. It helps teams manage vector collections, indexing, clustering, snapshots, point operations, payload metadata, and vector search from Konnectify workflows.
This integration is especially useful for AI, search, recommendation, and data operations teams that need to automate Qdrant collection management or run vector lookup workflows from other business systems.
New to Qdrant?
Learn how Qdrant stores vectors, payloads, collections, indexes, and search results.
Explore Qdrant docsNew to Konnectify?
Create workflows that connect vector database operations with apps, data pipelines, and AI systems.
Create a Konnectify accountWhat you can automate
•Create, update, inspect, and delete collections
•Manage aliases, indexes, shard keys, and cluster setup
•List snapshots and recover collections
•Upsert, delete, and batch update points
•Set, overwrite, delete, or clear payload metadata
•Run search, recommend, count, scroll, and hybrid query operations
API & Authentication
Authentication: API key credential connection
Konnectify connects using a user-supplied base_url and api_key. The connector sends the API key in the api-key request header. OAuth, PKCE, and refresh token flows are not supported in this connector.
Connection fields
- base_url: Qdrant cluster base URL, normalized without a trailing slash. Defaults to http://localhost:6333 when no value is supplied.
- api_key: Required credential sent in the api-key header for authenticated requests.
- Validation: Konnectify requires explicit connector fields; deeper schema and domain validation is enforced by the Qdrant API.
Important: JSON bodies must match Qdrant schemas
Many actions require body-style inputs such as collection_body, points_body, query_body, or selector objects. These must be valid JSON objects matching the Qdrant API schema for the target endpoint.
How to connect Quadrant to Konnectify
Prerequisites
- A reachable Qdrant cluster URL.
- An API key with permission to run the required collection, point, search, and administration actions.
- Valid JSON request bodies for any action that requires Qdrant API payloads.
Add Quadrant to a workflow
Create or open a workflow in Konnectify, add a step, and select Quadrant.
Enter connection fields
Provide the Qdrant base URL and API key. If no base URL is supplied, the connector helper defaults to http://localhost:6333.
Choose an action module
Select collection, indexing, cluster, point, payload, vector, search, recommendation, or query operations.
Map required inputs
Map collection_name and any required JSON body fields such as collection_body, points_body, query_body, or selector payloads.
Test and activate
Run a test request, confirm the Qdrant response contains status, time, and result, then turn on the workflow.
Triggers 0
No active Quadrant triggers are exported in the current v1.0.0 connector build.
Trigger Availability 0 triggers
No Active TriggersThe exported triggers object is empty and app metadata sets has_triggers=false.
Actions 34
Use actions to manage Qdrant collections, indexes, shards, clusters, snapshots, points, vectors, payloads, and query workflows.
Collection Lifecycle & Aliases 8 actions
GET /collections
List CollectionsRetrieves every collection name and metadata currently registered in Qdrant.
GET /collections/{collection_name}
Get Collection InfoFetches metadata for a collection, including vector config, shard counts, and statistics.
PUT /collections/{collection_name}
Create CollectionProvisions a new collection using a CreateCollection body from the Qdrant API spec.
PATCH /collections/{collection_name}
Update CollectionAdjusts collection parameters such as optimizer settings and other collection configuration.
DELETE /collections/{collection_name}
Delete CollectionDeletes a collection and its stored data.
GET /collections/{collection_name}/exists
Check Collection ExistsChecks whether a named collection exists.
POST /collections/aliases
Update AliasesAdds or removes collection aliases using ChangeAliasesOperation payloads.
GET /collections/{collection_name}/aliases
List Collection AliasesLists alias mappings for a collection so teams can audit routing coverage.
Indexing & Sharding 4 actions
PUT /collections/{collection_name}/index
Create Field IndexCreates a payload field index to accelerate filtering.
DELETE /collections/{collection_name}/index/{field_name}
Delete Field IndexRemoves a payload field index when it is no longer required.
PUT /collections/{collection_name}/shards
Create Shard KeyCreates a custom shard key mapping using the CreateShardingKey schema.
POST /collections/{collection_name}/shards/delete
Delete Shard KeyDeletes a custom shard key mapping using a DropShardingKey body.
Cluster & Snapshots 4 actions
GET /collections/{collection_name}/cluster
Get Cluster InfoShows replica and shard placement information for distributed deployments.
POST /collections/{collection_name}/cluster
Update Cluster SetupApplies cluster operations such as reshards or replica movement.
GET /collections/{collection_name}/snapshots
List Collection SnapshotsLists snapshots stored for a collection before recovery or review.
PUT /collections/{collection_name}/snapshots/recover
Recover From SnapshotRestores a collection from a snapshot body.
Points CRUD, Vectors & Payload 11 actions
GET /collections/{collection_name}/points/{id}
Get PointFetches one point by ID with vector, payload, and metadata.
POST /collections/{collection_name}/points
Get Multiple PointsFetches multiple points in one request using a PointRequest body.
PUT /collections/{collection_name}/points
Upsert PointsInserts or overwrites points with vectors and payload.
POST /collections/{collection_name}/points/delete
Delete PointsDeletes points by IDs, range, or filter using a PointsSelector body.
PUT /collections/{collection_name}/points/vectors
Update VectorsUpdates named vectors on selected points.
POST /collections/{collection_name}/points/vectors/delete
Delete VectorsRemoves named vectors from selected points.
POST /collections/{collection_name}/points/payload
Set PayloadSets payload fields on selected points.
PUT /collections/{collection_name}/points/payload
Overwrite PayloadOverwrites payload data for selected points.
POST /collections/{collection_name}/points/payload/delete
Delete Payload KeysRemoves specific payload keys or fields.
POST /collections/{collection_name}/points/payload/clear
Clear PayloadClears all payload from selected points.
POST /collections/{collection_name}/points/batch
Batch Update PointsRuns multiple point operations together, including upserts, payload changes, and vector updates.
Search, Recommendation & Query 7 actions
POST /collections/{collection_name}/points/scroll
Scroll PointsScrolls through points using filters and pagination.
POST /collections/{collection_name}/points/search
Search PointsRuns vector similarity search with query vectors and optional filters.
POST /collections/{collection_name}/points/search/batch
Batch SearchExecutes multiple search requests in one efficient batch.
POST /collections/{collection_name}/points/recommend
Recommend PointsFinds similar points using positive and negative examples.
POST /collections/{collection_name}/points/recommend/batch
Batch RecommendRuns multiple recommendation queries in one request.
POST /collections/{collection_name}/points/count
Count PointsCounts points matching a filter, optionally using exact counting.
POST /collections/{collection_name}/points/query
Hybrid QueryUses the newer Query API to combine search, recommendation, and filtering clauses.
Popular automations
Here are common Quadrant workflows you can build quickly with the available actions.
Create and populate a vector collection
Provision a collection, create any needed payload indexes, then upsert embedded points with payload metadata.
Create Collection → Create Field Index → Upsert Points
Refresh point payload for synced records
When an external record changes, update point payload fields or clear stale metadata from selected points.
Set Payload → Delete Payload Keys → Batch Update Points
Run semantic search from workflow data
Use an incoming query vector to find matching points, then route the top results to another system.
Search Points → Hybrid Query → Get Point
Recover a collection from a snapshot
List available snapshots, choose the correct snapshot, and recover the collection when needed.
List Collection Snapshots → Recover From Snapshot
FAQ
How does Konnectify authenticate with Quadrant?
The connector uses credential-based authentication with base_url and api_key. The API key is sent in the api-key request header.
Does this connector support OAuth or refresh tokens?
No. The document states that OAuth, PKCE, and refresh flows are not supported in this connector build.
Are there any triggers?
No active triggers are exported in v1.0.0. The app metadata sets has_triggers=false and the exported triggers object is empty.
What base URL should I use?
Use your Qdrant cluster base URL. The helper normalizes it without a trailing slash and defaults to http://localhost:6333 when no value is supplied.
What response fields do actions return?
Most documented actions return Qdrant-style response fields such as status, time, and result.
Who enforces detailed schema validation?
Konnectify validates explicit required fields such as collection_name and JSON body inputs. Deeper schema, payload, and domain validation is enforced by the Qdrant API.
Ready to automate your Quadrant workflows?
Connect Quadrant to Konnectify to automate vector database administration, point updates, and search workflows.
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