pinecone

Server path: /pinecone | Type: Application | PCID required: Yes

Tools

Tool	Description
`pinecone_configure_index`	Configure an index
`pinecone_create_backup`	Create a backup of an index
`pinecone_create_collection`	Create a collection
`pinecone_create_index`	Create an index
`pinecone_create_index_for_model`	Create an index with integrated embedding
`pinecone_create_index_from_backup_operation`	Create an index from a backup
`pinecone_delete_backup`	Delete a backup
`pinecone_delete_collection`	Delete a collection
`pinecone_delete_index`	Delete an index
`pinecone_describe_backup`	Describe a backup
`pinecone_describe_collection`	Describe a collection
`pinecone_describe_index`	Describe an index
`pinecone_describe_restore_job`	Describe a restore job
`pinecone_embed`	Generate vectors
`pinecone_get_model`	Describe a model
`pinecone_list_collections`	List collections
`pinecone_list_index_backups`	List backups for an index
`pinecone_list_indexes`	List indexes
`pinecone_list_models`	List available models
`pinecone_list_project_backups`	List backups for all indexes in a project
`pinecone_list_restore_jobs`	List restore jobs
`pinecone_rerank`	Rerank results

pinecone_configure_index

Configure an index Parameters:

Parameter	Type	Required	Default	Description
`index_name`	string	Yes	—	The name of the index to configure.
`deletion_protection`	string	No	—	Whether deletion protection is enabled/disabled for the index. Possible values: `disabled` or `enabled`.
`embed`	object	No	—	Configure the integrated inference embedding settings for this index. You can convert an existing index to an integrated index by specifying the embedding model and field_map. The index vector type and dimension must match the model vector type and dimension, and the index similarity metric must be supported by the model. Refer to the model guide for available models and model details. You can later change the embedding configuration to update the field map, read parameters, or write parameters. Once set, the model cannot be changed.
`spec`	object	No	—	The spec object defines how the index should be deployed. Only some attributes of an index’s spec may be updated. In general, you can modify settings related to scaling and configuration but you cannot change the cloud or region where the index is hosted.
`tags`	object	No	—	Custom user tags added to an index. Keys must be 80 characters or less. Values must be 120 characters or less. Keys must be alphanumeric, '', or ’-’. Values must be alphanumeric, ’;’, ’@’, '', ’-’, ’.’, ’+’, or ’ ’. To unset a key, set the value to be an empty string.

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for the authenticated connection"
    },
    "index_name": {
      "type": "string",
      "description": "The name of the index to configure."
    },
    "deletion_protection": {
      "type": "string",
      "description": "Whether [deletion protection](http://docs.pinecone.io/guides/manage-data/manage-indexes#configure-deletion-protection) is enabled/disabled for the index. Possible values: `disabled` or `enabled`."
    },
    "embed": {
      "type": "object",
      "description": "Configure the integrated inference embedding settings for this index.  You can convert an existing index to an integrated index by specifying the embedding model and field_map. The index vector type and dimension must match the model vector type and dimension, and the index similarity metric must be supported by the model. Refer to the [model guide](https://docs.pinecone.io/guides/index-data/create-an-index#embedding-models) for available models and model details.  You can later change the embedding configuration to update the field map, read parameters, or write parameters. Once set, the model cannot be changed.",
      "properties": {
        "model": {
          "type": "string",
          "description": "The name of the embedding model to use with the index. The index dimension and model dimension must match, and the index similarity metric must be supported by the model. The index embedding model cannot be changed once set."
        },
        "field_map": {
          "type": "object",
          "description": "Identifies the name of the text field from your document model that will be embedded."
        },
        "read_parameters": {
          "type": "object",
          "description": "The read parameters for the embedding model."
        },
        "write_parameters": {
          "type": "object",
          "description": "The write parameters for the embedding model."
        }
      }
    },
    "spec": {
      "description": "The spec object defines how the index should be deployed.  Only some attributes of an index's spec may be updated.  In general, you can modify settings related to scaling and  configuration but you cannot change the cloud or region  where the index is hosted."
    },
    "tags": {
      "type": "object",
      "description": "Custom user tags added to an index. Keys must be 80 characters or less. Values must be 120 characters or less. Keys must be alphanumeric, '_', or '-'.  Values must be alphanumeric, ';', '@', '_', '-', '.', '+', or ' '. To unset a key, set the value to be an empty string."
    }
  },
  "required": [
    "PCID",
    "index_name"
  ]
}

pinecone_create_backup

Create a backup of an index Parameters:

Parameter	Type	Required	Default	Description
`index_name`	string	Yes	—	Name of the index to backup
`description`	string	No	—	A description of the backup.
`name`	string	No	—	The name of the backup.

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for the authenticated connection"
    },
    "index_name": {
      "type": "string",
      "description": "Name of the index to backup"
    },
    "description": {
      "type": "string",
      "description": "A description of the backup."
    },
    "name": {
      "type": "string",
      "description": "The name of the backup."
    }
  },
  "required": [
    "PCID",
    "index_name"
  ]
}

pinecone_create_collection

Create a collection Parameters:

Parameter	Type	Required	Default	Description
`name`	string	Yes	—	The name of the collection to be created. Resource name must be 1-45 characters long, start and end with an alphanumeric character, and consist only of lower case alphanumeric characters or ’-’.
`source`	string	Yes	—	The name of the index to be used as the source for the collection.

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for the authenticated connection"
    },
    "name": {
      "type": "string",
      "description": "The name of the collection to be created. Resource name must be 1-45 characters long, start and end with an alphanumeric character, and consist only of lower case alphanumeric characters or '-'."
    },
    "source": {
      "type": "string",
      "description": "The name of the index to be used as the source for the collection."
    }
  },
  "required": [
    "PCID",
    "name",
    "source"
  ]
}

pinecone_create_index

Create an index Parameters:

Parameter	Type	Required	Default	Description
`deletion_protection`	string	No	—	Whether deletion protection is enabled/disabled for the index. Possible values: `disabled` or `enabled`.
`dimension`	integer	No	—	The dimensions of the vectors to be inserted in the index.
`metric`	string	No	—	The distance metric to be used for similarity search. You can use ‘euclidean’, ‘cosine’, or ‘dotproduct’. If the ‘vector_type’ is ‘sparse’, the metric must be ‘dotproduct’. If the `vector_type` is `dense`, the metric defaults to ‘cosine’. Possible values: `cosine`, `euclidean`, or `dotproduct`.
`name`	string	Yes	—	The name of the index. Resource name must be 1-45 characters long, start and end with an alphanumeric character, and consist only of lower case alphanumeric characters or ’-’.
`spec`	object	Yes	—	The spec object defines how the index should be deployed. For serverless indexes, you define only the cloud and region where the index should be hosted. For pod-based indexes, you define the environment where the index should be hosted, the pod type and size to use, and other index characteristics.
`tags`	object	No	—	Custom user tags added to an index. Keys must be 80 characters or less. Values must be 120 characters or less. Keys must be alphanumeric, '', or ’-’. Values must be alphanumeric, ’;’, ’@’, '', ’-’, ’.’, ’+’, or ’ ’. To unset a key, set the value to be an empty string.
`vector_type`	string	No	—	The index vector type. You can use ‘dense’ or ‘sparse’. If ‘dense’, the vector dimension must be specified. If ‘sparse’, the vector dimension should not be specified.

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for the authenticated connection"
    },
    "deletion_protection": {
      "type": "string",
      "description": "Whether [deletion protection](http://docs.pinecone.io/guides/manage-data/manage-indexes#configure-deletion-protection) is enabled/disabled for the index. Possible values: `disabled` or `enabled`."
    },
    "dimension": {
      "type": "integer",
      "description": "The dimensions of the vectors to be inserted in the index."
    },
    "metric": {
      "type": "string",
      "description": "The distance metric to be used for similarity search. You can use 'euclidean', 'cosine', or 'dotproduct'. If the 'vector_type' is 'sparse', the metric must be 'dotproduct'. If the `vector_type` is `dense`, the metric defaults to 'cosine'. Possible values: `cosine`, `euclidean`, or `dotproduct`."
    },
    "name": {
      "type": "string",
      "description": "The name of the index. Resource name must be 1-45 characters long, start and end with an alphanumeric character, and consist only of lower case alphanumeric characters or '-'."
    },
    "spec": {
      "type": "object",
      "description": "The spec object defines how the index should be deployed.  For serverless indexes, you define only the [cloud and region](http://docs.pinecone.io/guides/index-data/create-an-index#cloud-regions) where the index should be hosted. For pod-based indexes, you define the [environment](http://docs.pinecone.io/guides/indexes/pods/understanding-pod-based-indexes#pod-environments) where the index should be hosted, the [pod type and size](http://docs.pinecone.io/guides/indexes/pods/understanding-pod-based-indexes#pod-types) to use, and other index characteristics."
    },
    "tags": {
      "type": "object",
      "description": "Custom user tags added to an index. Keys must be 80 characters or less. Values must be 120 characters or less. Keys must be alphanumeric, '_', or '-'.  Values must be alphanumeric, ';', '@', '_', '-', '.', '+', or ' '. To unset a key, set the value to be an empty string."
    },
    "vector_type": {
      "type": "string",
      "description": "The index vector type. You can use 'dense' or 'sparse'. If 'dense', the vector dimension must be specified.  If 'sparse', the vector dimension should not be specified."
    }
  },
  "required": [
    "PCID",
    "name",
    "spec"
  ]
}

pinecone_create_index_for_model

Create an index with integrated embedding Parameters:

Parameter	Type	Required	Default	Description
`cloud`	string	Yes	—	The public cloud where you would like your index hosted. Possible values: `gcp`, `aws`, or `azure`.
`deletion_protection`	string	No	—	Whether deletion protection is enabled/disabled for the index. Possible values: `disabled` or `enabled`.
`embed`	object	Yes	—	Specify the integrated inference embedding configuration for the index. Once set the model cannot be changed, but you can later update the embedding configuration for an integrated inference index including field map, read parameters, or write parameters. Refer to the model guide for available models and model details.
`name`	string	Yes	—	The name of the index. Resource name must be 1-45 characters long, start and end with an alphanumeric character, and consist only of lower case alphanumeric characters or ’-’.
`read_capacity`	object	No	—	By default the index will be created with read capacity mode `OnDemand`. If you prefer to allocate dedicated read nodes for your workload, you must specify mode `Dedicated` and additional configurations for `node_type` and `scaling`.
`region`	string	Yes	—	The region where you would like your index to be created.
`schema`	object	No	—	Schema for the behavior of Pinecone’s internal metadata index. By default, all metadata is indexed; when `schema` is present, only fields which are present in the `fields` object with a `filterable: true` are indexed. Note that `filterable: false` is not currently supported.
`tags`	object	No	—	Custom user tags added to an index. Keys must be 80 characters or less. Values must be 120 characters or less. Keys must be alphanumeric, '', or ’-’. Values must be alphanumeric, ’;’, ’@’, '', ’-’, ’.’, ’+’, or ’ ’. To unset a key, set the value to be an empty string.

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for the authenticated connection"
    },
    "cloud": {
      "type": "string",
      "description": "The public cloud where you would like your index hosted. Possible values: `gcp`, `aws`, or `azure`."
    },
    "deletion_protection": {
      "type": "string",
      "description": "Whether [deletion protection](http://docs.pinecone.io/guides/manage-data/manage-indexes#configure-deletion-protection) is enabled/disabled for the index. Possible values: `disabled` or `enabled`."
    },
    "embed": {
      "type": "object",
      "description": "Specify the integrated inference embedding configuration for the index.  Once set the model cannot be changed, but you can later update the embedding configuration for an integrated inference index including field map, read parameters, or write parameters.  Refer to the [model guide](https://docs.pinecone.io/guides/index-data/create-an-index#embedding-models) for available models and model details.",
      "properties": {
        "model": {
          "type": "string",
          "description": "The name of the embedding model to use for the index."
        },
        "metric": {
          "type": "string",
          "description": "The distance metric to be used for similarity search. You can use 'euclidean', 'cosine', or 'dotproduct'. If not specified, the metric will be defaulted according to the model. Cannot be updated once set. Possible values: `cosine`, `euclidean`, or `dotproduct`."
        },
        "field_map": {
          "type": "object",
          "description": "Identifies the name of the text field from your document model that will be embedded."
        },
        "dimension": {
          "type": "integer",
          "description": "The dimension of embedding vectors produced for the index."
        },
        "read_parameters": {
          "type": "object",
          "description": "The read parameters for the embedding model."
        },
        "write_parameters": {
          "type": "object",
          "description": "The write parameters for the embedding model."
        }
      },
      "required": [
        "model",
        "field_map"
      ]
    },
    "name": {
      "type": "string",
      "description": "The name of the index. Resource name must be 1-45 characters long, start and end with an alphanumeric character, and consist only of lower case alphanumeric characters or '-'."
    },
    "read_capacity": {
      "description": "By default the index will be created with read capacity  mode `OnDemand`. If you prefer to allocate dedicated read  nodes for your workload, you must specify mode `Dedicated` and additional configurations for `node_type` and `scaling`."
    },
    "region": {
      "type": "string",
      "description": "The region where you would like your index to be created."
    },
    "schema": {
      "type": "object",
      "description": "Schema for the behavior of Pinecone's internal metadata index. By default, all metadata is indexed; when `schema` is present, only fields which are present in the `fields` object with a `filterable: true` are indexed. Note that `filterable: false` is not currently supported.",
      "properties": {
        "fields": {
          "type": "object",
          "description": "A map of metadata field names to their configuration. The field name must be a valid metadata field name. The field name must be unique."
        }
      },
      "required": [
        "fields"
      ]
    },
    "tags": {
      "type": "object",
      "description": "Custom user tags added to an index. Keys must be 80 characters or less. Values must be 120 characters or less. Keys must be alphanumeric, '_', or '-'.  Values must be alphanumeric, ';', '@', '_', '-', '.', '+', or ' '. To unset a key, set the value to be an empty string."
    }
  },
  "required": [
    "PCID",
    "cloud",
    "embed",
    "name",
    "region"
  ]
}

pinecone_create_index_from_backup_operation

Create an index from a backup Parameters:

Parameter	Type	Required	Default	Description
`backup_id`	string	Yes	—	The ID of the backup to create an index from.
`deletion_protection`	string	No	—	Whether deletion protection is enabled/disabled for the index. Possible values: `disabled` or `enabled`.
`name`	string	Yes	—	The name of the index. Resource name must be 1-45 characters long, start and end with an alphanumeric character, and consist only of lower case alphanumeric characters or ’-’.
`tags`	object	No	—	Custom user tags added to an index. Keys must be 80 characters or less. Values must be 120 characters or less. Keys must be alphanumeric, '', or ’-’. Values must be alphanumeric, ’;’, ’@’, '', ’-’, ’.’, ’+’, or ’ ’. To unset a key, set the value to be an empty string.

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for the authenticated connection"
    },
    "backup_id": {
      "type": "string",
      "description": "The ID of the backup to create an index from."
    },
    "deletion_protection": {
      "type": "string",
      "description": "Whether [deletion protection](http://docs.pinecone.io/guides/manage-data/manage-indexes#configure-deletion-protection) is enabled/disabled for the index. Possible values: `disabled` or `enabled`."
    },
    "name": {
      "type": "string",
      "description": "The name of the index. Resource name must be 1-45 characters long, start and end with an alphanumeric character, and consist only of lower case alphanumeric characters or '-'."
    },
    "tags": {
      "type": "object",
      "description": "Custom user tags added to an index. Keys must be 80 characters or less. Values must be 120 characters or less. Keys must be alphanumeric, '_', or '-'.  Values must be alphanumeric, ';', '@', '_', '-', '.', '+', or ' '. To unset a key, set the value to be an empty string."
    }
  },
  "required": [
    "PCID",
    "backup_id",
    "name"
  ]
}

pinecone_delete_backup

Delete a backup Parameters:

Parameter	Type	Required	Default	Description
`backup_id`	string	Yes	—	The ID of the backup to delete.

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for the authenticated connection"
    },
    "backup_id": {
      "type": "string",
      "description": "The ID of the backup to delete."
    }
  },
  "required": [
    "PCID",
    "backup_id"
  ]
}

pinecone_delete_collection

Delete a collection Parameters:

Parameter	Type	Required	Default	Description
`collection_name`	string	Yes	—	The name of the collection.

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for the authenticated connection"
    },
    "collection_name": {
      "type": "string",
      "description": "The name of the collection."
    }
  },
  "required": [
    "PCID",
    "collection_name"
  ]
}

pinecone_delete_index

Delete an index Parameters:

Parameter	Type	Required	Default	Description
`index_name`	string	Yes	—	The name of the index to delete.

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for the authenticated connection"
    },
    "index_name": {
      "type": "string",
      "description": "The name of the index to delete."
    }
  },
  "required": [
    "PCID",
    "index_name"
  ]
}

pinecone_describe_backup

Describe a backup Parameters:

Parameter	Type	Required	Default	Description
`backup_id`	string	Yes	—	The ID of the backup to describe.

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for the authenticated connection"
    },
    "backup_id": {
      "type": "string",
      "description": "The ID of the backup to describe."
    }
  },
  "required": [
    "PCID",
    "backup_id"
  ]
}

pinecone_describe_collection

Describe a collection Parameters:

Parameter	Type	Required	Default	Description
`collection_name`	string	Yes	—	The name of the collection to be described.

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for the authenticated connection"
    },
    "collection_name": {
      "type": "string",
      "description": "The name of the collection to be described."
    }
  },
  "required": [
    "PCID",
    "collection_name"
  ]
}

pinecone_describe_index

Describe an index Parameters:

Parameter	Type	Required	Default	Description
`index_name`	string	Yes	—	The name of the index to be described.

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for the authenticated connection"
    },
    "index_name": {
      "type": "string",
      "description": "The name of the index to be described."
    }
  },
  "required": [
    "PCID",
    "index_name"
  ]
}

pinecone_describe_restore_job

Describe a restore job Parameters:

Parameter	Type	Required	Default	Description
`job_id`	string	Yes	—	The ID of the restore job to describe.

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for the authenticated connection"
    },
    "job_id": {
      "type": "string",
      "description": "The ID of the restore job to describe."
    }
  },
  "required": [
    "PCID",
    "job_id"
  ]
}

pinecone_embed

Generate vectors Parameters:

Parameter	Type	Required	Default	Description
`inputs`	object[]	Yes	—	List of inputs to generate embeddings for.
`model`	string	Yes	—	The model to use for embedding generation.
`parameters`	object	No	—	Additional model-specific parameters. Refer to the model guide for available model parameters.

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for the authenticated connection"
    },
    "inputs": {
      "type": "array",
      "items": {
        "type": "object"
      },
      "description": "List of inputs to generate embeddings for."
    },
    "model": {
      "type": "string",
      "description": "The [model](https://docs.pinecone.io/guides/index-data/create-an-index#embedding-models) to use for embedding generation."
    },
    "parameters": {
      "type": "object",
      "description": "Additional model-specific parameters. Refer to the [model guide](https://docs.pinecone.io/guides/index-data/create-an-index#embedding-models) for available model parameters."
    }
  },
  "required": [
    "PCID",
    "inputs",
    "model"
  ]
}

pinecone_get_model

Describe a model Parameters:

Parameter	Type	Required	Default	Description
`model_name`	string	Yes	—	The name of the model to look up.

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for the authenticated connection"
    },
    "model_name": {
      "type": "string",
      "description": "The name of the model to look up."
    }
  },
  "required": [
    "PCID",
    "model_name"
  ]
}

pinecone_list_collections

List collections

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for the authenticated connection"
    }
  },
  "required": [
    "PCID"
  ]
}

pinecone_list_index_backups

List backups for an index Parameters:

Parameter	Type	Required	Default	Description
`index_name`	string	Yes	—	Name of the backed up index
`limit`	integer	No	—	The number of results to return per page.
`paginationToken`	string	No	—	The token to use to retrieve the next page of results.

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for the authenticated connection"
    },
    "index_name": {
      "type": "string",
      "description": "Name of the backed up index"
    },
    "limit": {
      "type": "integer",
      "description": "The number of results to return per page."
    },
    "paginationToken": {
      "type": "string",
      "description": "The token to use to retrieve the next page of results."
    }
  },
  "required": [
    "PCID",
    "index_name"
  ]
}

pinecone_list_indexes

List indexes

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for the authenticated connection"
    }
  },
  "required": [
    "PCID"
  ]
}

pinecone_list_models

List available models Parameters:

Parameter	Type	Required	Default	Description
`type`	string	No	—	Filter models by type (‘embed’ or ‘rerank’).
`vector_type`	string	No	—	Filter embedding models by vector type (‘dense’ or ‘sparse’). Only relevant when `type=embed`.

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for the authenticated connection"
    },
    "type": {
      "type": "string",
      "description": "Filter models by type ('embed' or 'rerank')."
    },
    "vector_type": {
      "type": "string",
      "description": "Filter embedding models by vector type ('dense' or 'sparse'). Only relevant when `type=embed`."
    }
  },
  "required": [
    "PCID"
  ]
}

pinecone_list_project_backups

List backups for all indexes in a project Parameters:

Parameter	Type	Required	Default	Description
`limit`	integer	No	—	The number of results to return per page.
`paginationToken`	string	No	—	The token to use to retrieve the next page of results.

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for the authenticated connection"
    },
    "limit": {
      "type": "integer",
      "description": "The number of results to return per page."
    },
    "paginationToken": {
      "type": "string",
      "description": "The token to use to retrieve the next page of results."
    }
  },
  "required": [
    "PCID"
  ]
}

pinecone_list_restore_jobs

List restore jobs Parameters:

Parameter	Type	Required	Default	Description
`limit`	integer	No	—	The number of results to return per page.
`paginationToken`	string	No	—	The token to use to retrieve the next page of results.

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for the authenticated connection"
    },
    "limit": {
      "type": "integer",
      "description": "The number of results to return per page."
    },
    "paginationToken": {
      "type": "string",
      "description": "The token to use to retrieve the next page of results."
    }
  },
  "required": [
    "PCID"
  ]
}

pinecone_rerank

Rerank results Parameters:

Parameter	Type	Required	Default	Description
`documents`	object[]	Yes	—	The documents to rerank.
`model`	string	Yes	—	The model to use for reranking.
`parameters`	object	No	—	Additional model-specific parameters. Refer to the model guide for available model parameters.
`query`	string	Yes	—	The query to rerank documents against.
`rank_fields`	string[]	No	—	The field(s) to consider for reranking. If not provided, the default is `["text"]`. The number of fields supported is model-specific.
`return_documents`	boolean	No	—	Whether to return the documents in the response.
`top_n`	integer	No	—	The number of results to return sorted by relevance. Defaults to the number of inputs.

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for the authenticated connection"
    },
    "documents": {
      "type": "array",
      "items": {
        "type": "object"
      },
      "description": "The documents to rerank."
    },
    "model": {
      "type": "string",
      "description": "The [model](https://docs.pinecone.io/guides/search/rerank-results#reranking-models) to use for reranking."
    },
    "parameters": {
      "type": "object",
      "description": "Additional model-specific parameters. Refer to the [model guide](https://docs.pinecone.io/guides/search/rerank-results#reranking-models) for available model parameters."
    },
    "query": {
      "type": "string",
      "description": "The query to rerank documents against."
    },
    "rank_fields": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "The field(s) to consider for reranking. If not provided, the default is `[\"text\"]`.  The number of fields supported is [model-specific](https://docs.pinecone.io/guides/search/rerank-results#reranking-models)."
    },
    "return_documents": {
      "type": "boolean",
      "description": "Whether to return the documents in the response."
    },
    "top_n": {
      "type": "integer",
      "description": "The number of results to return sorted by relevance. Defaults to the number of inputs."
    }
  },
  "required": [
    "PCID",
    "documents",
    "model",
    "query"
  ]
}

Triggers API

Platform API

Embedded MCP Servers

Application MCP Servers

Skills Guides

Tools

pinecone_configure_index

pinecone_create_backup

pinecone_create_collection

pinecone_create_index

pinecone_create_index_for_model

pinecone_create_index_from_backup_operation

pinecone_delete_backup

pinecone_delete_collection

pinecone_delete_index

pinecone_describe_backup

pinecone_describe_collection

pinecone_describe_index

pinecone_describe_restore_job

pinecone_embed

pinecone_get_model

pinecone_list_collections

pinecone_list_index_backups

pinecone_list_indexes

pinecone_list_models

pinecone_list_project_backups

pinecone_list_restore_jobs

pinecone_rerank

Triggers API

Platform API

Embedded MCP Servers

Application MCP Servers

Skills Guides

​Tools

​pinecone_configure_index

​pinecone_create_backup

​pinecone_create_collection

​pinecone_create_index

​pinecone_create_index_for_model

​pinecone_create_index_from_backup_operation

​pinecone_delete_backup

​pinecone_delete_collection

​pinecone_delete_index

​pinecone_describe_backup

​pinecone_describe_collection

​pinecone_describe_index

​pinecone_describe_restore_job

​pinecone_embed

​pinecone_get_model

​pinecone_list_collections

​pinecone_list_index_backups

​pinecone_list_indexes

​pinecone_list_models

​pinecone_list_project_backups

​pinecone_list_restore_jobs

​pinecone_rerank

Tools

pinecone_configure_index

pinecone_create_backup

pinecone_create_collection

pinecone_create_index

pinecone_create_index_for_model

pinecone_create_index_from_backup_operation

pinecone_delete_backup

pinecone_delete_collection

pinecone_delete_index

pinecone_describe_backup

pinecone_describe_collection

pinecone_describe_index

pinecone_describe_restore_job

pinecone_embed

pinecone_get_model

pinecone_list_collections

pinecone_list_index_backups

pinecone_list_indexes

pinecone_list_models

pinecone_list_project_backups

pinecone_list_restore_jobs

pinecone_rerank