MCP Tools Reference: vectorsearch.googleapis.com

Tool: get_collection

Retrieves the schema and details of a specific collection.

The following code sample shows how to use curl to call the get_collection MCP tool.

Curl Request 
curl --location 'https://vectorsearch.googleapis.com/mcp' \
--header 'content-type: application/json' \
--header 'accept: application/json, text/event-stream' \
--data '{
  "method": "tools/call",
  "params": {
    "name": "get_collection",
    "arguments": {
      // Provide these details according to the MCP tool specification.
    }
  },
  "jsonrpc": "2.0",
  "id": 1
}'

Input Schema

Message for getting a Collection

GetCollectionRequest

JSON representation 
{
  "name": string
}
Fields
name

string

Required. Name of the resource

Output Schema

Message describing Collection object

Collection

JSON representation 
{
  "name": string,
  "displayName": string,
  "description": string,
  "createTime": string,
  "updateTime": string,
  "labels": {
    string: string,
    ...
  },
  "vectorSchema": {
    string: {
      object (VectorField)
    },
    ...
  },
  "dataSchema": {
    object
  },
  "encryptionSpec": {
    object (EncryptionSpec)
  }
}
Fields
name

string

Identifier. name of resource
displayName

string

Optional. User-specified display name of the collection
description

string

Optional. User-specified description of the collection
createTime

string (Timestamp format)

Output only. [Output only] Create time stamp

Uses RFC 3339, where generated output will always be Z-normalized and use 0, 3, 6 or 9 fractional digits. Offsets other than "Z" are also accepted. Examples: "2014-10-02T15:01:23Z", "2014-10-02T15:01:23.045123456Z" or "2014-10-02T15:01:23+05:30".
updateTime

string (Timestamp format)

Output only. [Output only] Update time stamp

Uses RFC 3339, where generated output will always be Z-normalized and use 0, 3, 6 or 9 fractional digits. Offsets other than "Z" are also accepted. Examples: "2014-10-02T15:01:23Z", "2014-10-02T15:01:23.045123456Z" or "2014-10-02T15:01:23+05:30".
labels

map (key: string, value: string)

Optional. Labels as key value pairs.

An object containing a list of "key": value pairs. Example: { "name": "wrench", "mass": "1.3kg", "count": "3" }.
vectorSchema

map (key: string, value: object (VectorField))

Optional. Schema for vector fields. Only vector fields in this schema will be searchable. Field names must contain only alphanumeric characters, underscores, and hyphens.

An object containing a list of "key": value pairs. Example: { "name": "wrench", "mass": "1.3kg", "count": "3" }.
dataSchema

object (Struct format)

Optional. JSON Schema for data. Field names must contain only alphanumeric characters, underscores, and hyphens. The schema must be compliant with JSON Schema Draft 7.
encryptionSpec

object (EncryptionSpec)

Optional. Immutable. Specifies the customer-managed encryption key spec for a Collection. If set, this Collection and all sub-resources of this Collection will be secured by this key.

Timestamp

JSON representation 
{
  "seconds": string,
  "nanos": integer
}
Fields
seconds

string (int64 format)

Represents seconds of UTC time since Unix epoch 1970-01-01T00:00:00Z. Must be between -62135596800 and 253402300799 inclusive (which corresponds to 0001-01-01T00:00:00Z to 9999-12-31T23:59:59Z).
nanos

integer

Non-negative fractions of a second at nanosecond resolution. This field is the nanosecond portion of the duration, not an alternative to seconds. Negative second values with fractions must still have non-negative nanos values that count forward in time. Must be between 0 and 999,999,999 inclusive.

LabelsEntry

JSON representation 
{
  "key": string,
  "value": string
}
Fields
key

string
value

string

VectorSchemaEntry

JSON representation 
{
  "key": string,
  "value": {
    object (VectorField)
  }
}
Fields
key

string
value

object (VectorField)

VectorField

JSON representation 
{

  // Union field vector_type_config can be only one of the following:
  "denseVector": {
    object (DenseVectorField)
  },
  "sparseVector": {
    object (SparseVectorField)
  }
  // End of list of possible types for union field vector_type_config.
}
Fields
Union field vector_type_config. Vector type configuration. vector_type_config can be only one of the following:
denseVector

object (DenseVectorField)

Dense vector field.
sparseVector

object (SparseVectorField)

Sparse vector field.

DenseVectorField

JSON representation 
{
  "dimensions": integer,
  "vertexEmbeddingConfig": {
    object (VertexEmbeddingConfig)
  }
}
Fields
dimensions

integer

Dimensionality of the vector field.
vertexEmbeddingConfig

object (VertexEmbeddingConfig)

Optional. Configuration for generating embeddings for the vector field. If not specified, the embedding field must be populated in the DataObject.

VertexEmbeddingConfig

JSON representation 
{
  "modelId": string,
  "textTemplate": string,
  "taskType": enum (EmbeddingTaskType)
}
Fields
modelId

string

Required. Required: ID of the embedding model to use. See https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#embeddings-models for the list of supported models.
textTemplate

string

Optional. Text template for the input to the model. The template must contain one or more references to fields in the DataObject, e.g.: "Movie Title: {title} ---- Movie Plot: {plot}".

Required when using the text-only path.
taskType

enum (EmbeddingTaskType)

Optional. Optional: Task type for the embeddings. Required for text-only embedding models, see https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/embeddings/task-types Not needed for multi modal embedding models, see https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/embeddings/get-multimodal-embeddings#specify-task-instructions

Struct

JSON representation 
{
  "fields": {
    string: value,
    ...
  }
}
Fields
fields

map (key: string, value: value (Value format))

Unordered map of dynamically typed values.

An object containing a list of "key": value pairs. Example: { "name": "wrench", "mass": "1.3kg", "count": "3" }.

FieldsEntry

JSON representation 
{
  "key": string,
  "value": value
}
Fields
key

string
value

value (Value format)

Value

JSON representation 
{

  // Union field kind can be only one of the following:
  "nullValue": null,
  "numberValue": number,
  "stringValue": string,
  "boolValue": boolean,
  "structValue": {
    object
  },
  "listValue": array
  // End of list of possible types for union field kind.
}
Fields
Union field kind. The kind of value. kind can be only one of the following:
nullValue

null

Represents a JSON null.
numberValue

number

Represents a JSON number. Must not be NaN, Infinity or -Infinity, since those are not supported in JSON. This also cannot represent large Int64 values, since JSON format generally does not support them in its number type.
stringValue

string

Represents a JSON string.
boolValue

boolean

Represents a JSON boolean (true or false literal in JSON).
structValue

object (Struct format)

Represents a JSON object.
listValue

array (ListValue format)

Represents a JSON array.

ListValue

JSON representation 
{
  "values": [
    value
  ]
}
Fields
values[]

value (Value format)

Repeated field of dynamically typed values.

EncryptionSpec

JSON representation 
{
  "cryptoKeyName": string
}
Fields
cryptoKeyName

string

Required. Resource name of the Cloud KMS key used to protect the resource.

The Cloud KMS key must be in the same region as the resource. It must have the format projects/{project}/locations/{location}/keyRings/{key_ring}/cryptoKeys/{crypto_key}.

EmbeddingTaskType

Represents the task the embeddings will be used for.

Enums
EMBEDDING_TASK_TYPE_UNSPECIFIED Unspecified task type.
RETRIEVAL_QUERY Specifies the given text is a query in a search/retrieval setting.
RETRIEVAL_DOCUMENT Specifies the given text is a document from the corpus being searched.
SEMANTIC_SIMILARITY Specifies the given text will be used for STS.
CLASSIFICATION Specifies that the given text will be classified.
CLUSTERING Specifies that the embeddings will be used for clustering.
QUESTION_ANSWERING Specifies that the embeddings will be used for question answering.
FACT_VERIFICATION Specifies that the embeddings will be used for fact verification.
CODE_RETRIEVAL_QUERY Specifies that the embeddings will be used for code retrieval.

NullValue

Represents a JSON null.

NullValue is a sentinel, using an enum with only one value to represent the null value for the Value type union.

A field of type NullValue with any value other than 0 is considered invalid. Most ProtoJSON serializers will emit a Value with a null_value set as a JSON null regardless of the integer value, and so will round trip to a 0 value.

Enums
NULL_VALUE Null value.

Tool Annotations

Tool annotations are sent to MCP clients to describe the basic risk of a given tool. Most clients treat these hints as untrusted, but they can be used to decide when a confirmation prompt might be sent to a user.

Along with the title string, the following boolean hints are defined as follows:

  • readOnlyHint: If true, the tool doesn't modify its environment. Default: false.
  • destructiveHint: If true, then the tool can perform destructive actions. If false, then the tool can only perform additive actions. Default: true.
  • idempotentHint: If true, then calling the tool repeatedly with the same arguments will have no additional effect on its environment. Default: false.
  • openWorldHint: If true, then the tool can interact with an 'open world' of external entities. If false, then the tool can only interact with internal entities. For example, a web search tool would be open world, while a memory tool would not be open world.

Destructive Hint: ❌ | Idempotent Hint: ✅ | Read Only Hint: ✅ | Open World Hint: ❌