Work with this as data
Every API here is available over the APIs.io API and to AI agents over MCP.
MCP server
One button, every client — Claude, Cursor, VS Code and the rest.
https://apis.io/mcp
Tools for apis
7 MCP tools reach this
find_apisBrowse and filter every API in the catalog.get_api_artifactsOne API's artifacts, grouped by type.get_openapiThe primary OpenAPI for this API.find_similar_apisAPIs that look like this one.apis_io_searchSTART HERE — APIs, providers and tags for one query, each with its total.resolveTurn a domain, URL or GitHub org into the provider it belongs to.find_cohortsEvery scored population of providers in the catalog.
Call it yourself
curl for this page
This API
curl "https://apis.io/api/v1/apis/qdrant-beta-api"
All apis
curl "https://apis.io/api/v1/apis?limit=25"
Discovery needs no key. Ratings and market analysis are Pro.
Get an API key
Free tier, no form to fill in. Signing in shares your email address with us — we store it to create your key and to recognise you if you sign in with another provider. See our Privacy Policy and Terms.
A second provider on the same verified email joins the account you already have.
OpenAPI Specification
openapi: 3.2.0
info:
title: Qdrant Aliases Beta API
description: "API description for Qdrant vector search engine.\n\nThis document describes CRUD and search operations on collections of points (vectors with payload).\n\nQdrant supports any combinations of `should`, `min_should`, `must` and `must_not` conditions, which makes it possible to use in applications when object could not be described solely by vector. It could be location features, availability flags, and other custom properties businesses should take into account.\n## Examples\nThis examples cover the most basic use-cases - collection creation and basic vector search.\n### Create collection\nFirst - let's create a collection with dot-production metric.\n```\ncurl -X PUT 'http://localhost:6333/collections/test_collection' \\\n -H 'Content-Type: application/json' \\\n --data-raw '{\n \"vectors\": {\n \"size\": 4,\n \"distance\": \"Dot\"\n }\n }'\n\n```\nExpected response:\n```\n{\n \"result\": true,\n \"status\": \"ok\",\n \"time\": 0.031095451\n}\n```\nWe can ensure that collection was created:\n```\ncurl 'http://localhost:6333/collections/test_collection'\n```\nExpected response:\n```\n{\n \"result\": {\n \"status\": \"green\",\n \"segments_count\": 5,\n \"disk_data_size\": 0,\n \"ram_data_size\": 0,\n \"config\": {\n \"params\": {\n \"vectors\": {\n \"size\": 4,\n \"distance\": \"Dot\"\n }\n },\n \"hnsw_config\": {\n \"m\": 16,\n \"ef_construct\": 100,\n \"full_scan_threshold\": 10000\n },\n \"optimizer_config\": {\n \"deleted_threshold\": 0.2,\n \"vacuum_min_vector_number\": 1000,\n \"default_segment_number\": 2,\n \"max_segment_size\": null,\n \"memmap_threshold\": null,\n \"indexing_threshold\": 20000,\n \"flush_interval_sec\": 5,\n \"max_optimization_threads\": null\n },\n \"wal_config\": {\n \"wal_capacity_mb\": 32,\n \"wal_segments_ahead\": 0\n }\n }\n },\n \"status\": \"ok\",\n \"time\": 2.1199e-05\n}\n```\n\n### Add points\nLet's now add vectors with some payload:\n```\ncurl -L -X PUT 'http://localhost:6333/collections/test_collection/points?wait=true' \\ -H 'Content-Type: application/json' \\ --data-raw '{\n \"points\": [\n {\"id\": 1, \"vector\": [0.05, 0.61, 0.76, 0.74], \"payload\": {\"city\": \"Berlin\"}},\n {\"id\": 2, \"vector\": [0.19, 0.81, 0.75, 0.11], \"payload\": {\"city\": [\"Berlin\", \"London\"] }},\n {\"id\": 3, \"vector\": [0.36, 0.55, 0.47, 0.94], \"payload\": {\"city\": [\"Berlin\", \"Moscow\"] }},\n {\"id\": 4, \"vector\": [0.18, 0.01, 0.85, 0.80], \"payload\": {\"city\": [\"London\", \"Moscow\"] }},\n {\"id\": 5, \"vector\": [0.24, 0.18, 0.22, 0.44], \"payload\": {\"count\": [0]}},\n {\"id\": 6, \"vector\": [0.35, 0.08, 0.11, 0.44]}\n ]\n}'\n```\nExpected response:\n```\n{\n \"result\": {\n \"operation_id\": 0,\n \"status\": \"completed\"\n },\n \"status\": \"ok\",\n \"time\": 0.000206061\n}\n```\n### Search with filtering\nLet's start with a basic request:\n```\ncurl -L -X POST 'http://localhost:6333/collections/test_collection/points/search' \\ -H 'Content-Type: application/json' \\ --data-raw '{\n \"vector\": [0.2,0.1,0.9,0.7],\n \"top\": 3\n}'\n```\nExpected response:\n```\n{\n \"result\": [\n { \"id\": 4, \"score\": 1.362, \"payload\": null, \"version\": 0 },\n { \"id\": 1, \"score\": 1.273, \"payload\": null, \"version\": 0 },\n { \"id\": 3, \"score\": 1.208, \"payload\": null, \"version\": 0 }\n ],\n \"status\": \"ok\",\n \"time\": 0.000055785\n}\n```\nBut result is different if we add a filter:\n```\ncurl -L -X POST 'http://localhost:6333/collections/test_collection/points/search' \\ -H 'Content-Type: application/json' \\ --data-raw '{\n \"filter\": {\n \"should\": [\n {\n \"key\": \"city\",\n \"match\": {\n \"value\": \"London\"\n }\n }\n ]\n },\n \"vector\": [0.2, 0.1, 0.9, 0.7],\n \"top\": 3\n}'\n```\nExpected response:\n```\n{\n \"result\": [\n { \"id\": 4, \"score\": 1.362, \"payload\": null, \"version\": 0 },\n { \"id\": 2, \"score\": 0.871, \"payload\": null, \"version\": 0 }\n ],\n \"status\": \"ok\",\n \"time\": 0.000093972\n}\n```\n"
contact:
email: andrey@vasnetsov.com
license:
name: Apache 2.0
url: http://www.apache.org/licenses/LICENSE-2.0.html
version: master
servers:
- url: '{protocol}://{hostname}:{port}'
variables:
protocol:
enum:
- http
- https
default: http
hostname:
default: localhost
port:
default: '6333'
security:
- api-key: []
- bearerAuth: []
- {}
tags:
- name: Beta
description: Beta features, do not depend on these yet.
paths:
/issues:
get:
summary: Get issues
description: Get a report of performance issues and configuration suggestions
operationId: get_issues
tags:
- Beta
responses:
'200':
description: Successful response
content:
application/json:
schema:
type: object
4XX:
description: error
delete:
summary: Clear issues
description: Removes all issues reported so far
operationId: clear_issues
tags:
- Beta
responses:
default:
description: error
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorResponse'
4XX:
description: error
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorResponse'
'200':
description: successful operation
content:
application/json:
schema:
type: object
properties:
usage:
default: null
anyOf:
- $ref: '#/components/schemas/Usage'
- {}
time:
type: number
format: float
description: Time spent to process this request
example: 0.002
status:
type: string
example: ok
result:
type: boolean
components:
schemas:
ErrorResponse:
type: object
properties:
time:
type: number
format: float
description: Time spent to process this request
status:
type: object
properties:
error:
type: string
description: Description of the occurred error.
result:
type:
- object
- 'null'
InferenceUsage:
type: object
required:
- models
properties:
models:
type: object
additionalProperties:
$ref: '#/components/schemas/ModelUsage'
HardwareUsage:
description: Usage of the hardware resources, spent to process the request
type: object
required:
- cpu
- payload_index_io_read
- payload_index_io_write
- payload_io_read
- payload_io_write
- vector_io_read
- vector_io_write
properties:
cpu:
type: integer
format: uint
minimum: 0
payload_io_read:
type: integer
format: uint
minimum: 0
payload_io_write:
type: integer
format: uint
minimum: 0
payload_index_io_read:
type: integer
format: uint
minimum: 0
payload_index_io_write:
type: integer
format: uint
minimum: 0
vector_io_read:
type: integer
format: uint
minimum: 0
vector_io_write:
type: integer
format: uint
minimum: 0
Usage:
description: Usage of the hardware resources, spent to process the request
type: object
properties:
hardware:
anyOf:
- $ref: '#/components/schemas/HardwareUsage'
- {}
inference:
anyOf:
- $ref: '#/components/schemas/InferenceUsage'
- {}
ModelUsage:
type: object
required:
- tokens
properties:
tokens:
type: integer
format: uint64
minimum: 0
securitySchemes:
api-key:
type: apiKey
in: header
name: api-key
description: Authorization key, either read-write or read-only
bearerAuth:
type: http
scheme: bearer
externalDocs:
description: Find out more about Qdrant applications and demo
url: https://qdrant.tech/documentation/