Pinecone

Pinecone MCP Server for Cloudflare Workers

Available Tools

34 tools available in the Pinecone MCP server. Each tool can be called by AI assistants to perform specific actions.

pinecone_describe_collection

Get detailed information about a specific collection.

Args:

collectionName: The name of the collection

Returns the collection details including name, size, status, dimension, and vector count.

{
  "type": "object",
  "required": [
    "collectionName"
  ],
  "properties": {
    "collectionName": {
      "type": "string",
      "description": "Collection name"
    }
  }
}

pinecone_describe_restore_job

Get detailed information about a restore job.

Args:

restoreId: The restore job ID

Returns restore job details including status and progress.

{
  "type": "object",
  "required": [
    "restoreId"
  ],
  "properties": {
    "restoreId": {
      "type": "string",
      "description": "Restore job ID"
    }
  }
}

pinecone_delete_collection

Delete a collection.

Args:

collectionName: The name of the collection to delete

WARNING: This operation is irreversible.

{
  "type": "object",
  "required": [
    "collectionName"
  ],
  "properties": {
    "collectionName": {
      "type": "string",
      "description": "Collection name to delete"
    }
  }
}

pinecone_list_backups

List backups in the project.

Args:

indexName: Optional - filter backups for a specific index

Returns an array of backup objects with status, metadata, and size information.

{
  "type": "object",
  "properties": {
    "indexName": {
      "type": "string",
      "description": "Filter by index name"
    }
  }
}

pinecone_create_backup

Create a backup of an index.

Args:

indexName: The name of the index to backup
name: Optional name for the backup
description: Optional description

Returns the backup details.

{
  "type": "object",
  "required": [
    "indexName"
  ],
  "properties": {
    "name": {
      "type": "string",
      "description": "Backup name"
    },
    "indexName": {
      "type": "string",
      "description": "Index name to backup"
    },
    "description": {
      "type": "string",
      "description": "Backup description"
    }
  }
}

pinecone_describe_backup

Get detailed information about a specific backup.

Args:

backupId: The backup ID

Returns backup details including status, size, and metadata.

{
  "type": "object",
  "required": [
    "backupId"
  ],
  "properties": {
    "backupId": {
      "type": "string",
      "description": "Backup ID"
    }
  }
}

pinecone_delete_backup

Delete a backup.

Args:

backupId: The backup ID to delete

WARNING: This operation is irreversible.

{
  "type": "object",
  "required": [
    "backupId"
  ],
  "properties": {
    "backupId": {
      "type": "string",
      "description": "Backup ID to delete"
    }
  }
}

pinecone_create_index_from_backup

Create a new index from a backup.

Args:

name: Name for the new index
backupId: The backup ID to restore from
deletionProtection: Optional deletion protection setting
tags: Optional custom tags

Returns the new index configuration.

{
  "type": "object",
  "required": [
    "name"
  ],
  "properties": {
    "name": {
      "type": "string",
      "description": "New index name"
    },
    "tags": {
      "type": "object",
      "description": "Custom tags"
    },
    "backupId": {
      "type": "string",
      "description": "Backup ID to restore from"
    }
  }
}

pinecone_list_restore_jobs

List all restore jobs in the project.

Returns an array of restore job objects with status and progress information.

{
  "type": "object",
  "properties": {}
}

pinecone_list_collections

List all collections in the project.

Returns an array of collection objects with name, size, status, dimension, and vector count.

{
  "type": "object",
  "properties": {}
}

pinecone_create_collection

Create a new collection from an existing index.

Args:

name: Collection name (1-45 chars, lowercase alphanumeric or hyphens)
source: Name of the source index to create collection from

The collection will be a static snapshot of the source index.

{
  "type": "object",
  "required": [
    "name",
    "source"
  ],
  "properties": {
    "name": {
      "type": "string",
      "description": "Collection name"
    },
    "source": {
      "type": "string",
      "description": "Source index name"
    }
  }
}

pinecone_start_import

Start a bulk import operation from cloud storage.

Args:

indexName: The name of the index to import into
uri: The URI of the data to import (e.g., s3://bucket/path/)
integrationId: Optional integration ID for cloud storage access
errorMode: How to handle errors ('abort' or 'continue')

Returns the import job details.

{
  "type": "object",
  "required": [
    "indexName",
    "uri"
  ],
  "properties": {
    "uri": {
      "type": "string",
      "description": "Source data URI"
    },
    "errorMode": {
      "enum": [
        "abort",
        "continue"
      ],
      "type": "string",
      "description": "Error handling mode"
    },
    "indexName": {
      "type": "string",
      "description": "Index name"
    },
    "integrationId": {
      "type": "string",
      "description": "Cloud storage integration ID"
    }
  }
}

pinecone_list_imports

List all import operations for an index.

Args:

indexName: The name of the index

Returns an array of import job objects with status and progress information.

{
  "type": "object",
  "required": [
    "indexName"
  ],
  "properties": {
    "indexName": {
      "type": "string",
      "description": "Index name"
    }
  }
}

pinecone_describe_import

Get detailed information about an import operation.

Args:

indexName: The name of the index
importId: The import job ID

Returns import job details including status, progress, and any errors.

{
  "type": "object",
  "required": [
    "indexName",
    "importId"
  ],
  "properties": {
    "importId": {
      "type": "string",
      "description": "Import job ID"
    },
    "indexName": {
      "type": "string",
      "description": "Index name"
    }
  }
}

pinecone_cancel_import

Cancel a running import operation.

Args:

indexName: The name of the index
importId: The import job ID to cancel

Note: Vectors already imported before cancellation will remain in the index.

{
  "type": "object",
  "required": [
    "indexName",
    "importId"
  ],
  "properties": {
    "importId": {
      "type": "string",
      "description": "Import job ID to cancel"
    },
    "indexName": {
      "type": "string",
      "description": "Index name"
    }
  }
}

pinecone_list_indexes

List all Pinecone indexes in the project.

Returns an array of index objects with name, dimension, metric, host, spec, and status.

{
  "type": "object",
  "properties": {}
}

pinecone_create_index

Create a new Pinecone index.

Args:

name: Index name (1-45 chars, lowercase alphanumeric or hyphens)
dimension: Vector dimension (1-20000)
metric: Distance metric (cosine, euclidean, dotproduct). Default: cosine
cloud: Cloud provider (aws, gcp, azure) for serverless
region: Cloud region for serverless
environment: Pod environment (for pod-based indexes)
podType: Pod type like p1.x1 (for pod-based indexes)
pods: Number of pods (for pod-based indexes)
replicas: Number of replicas (for pod-based indexes)
deletionProtection: Enable deletion protection (enabled/disabled)

Returns the created index configuration.

{
  "type": "object",
  "required": [
    "name"
  ],
  "properties": {
    "name": {
      "type": "string",
      "description": "Index name"
    },
    "pods": {
      "type": "integer",
      "minimum": 1,
      "description": "Number of pods"
    },
    "tags": {
      "type": "object",
      "description": "Custom tags"
    },
    "cloud": {
      "enum": [
        "aws",
        "gcp",
        "azure"
      ],
      "type": "string",
      "description": "Cloud provider for serverless"
    },
    "region": {
      "type": "string",
      "description": "Cloud region for serverless"
    },
    "podType": {
      "type": "string",
      "description": "Pod type (e.g., p1.x1)"
    },
    "replicas": {
      "type": "integer",
      "minimum": 1,
      "description": "Number of replicas"
    },
    "dimension": {
      "type": "integer",
      "maximum": 20000,
      "minimum": 1,
      "description": "Vector dimension"
    },
    "environment": {
      "type": "string",
      "description": "Pod environment"
    }
  }
}

pinecone_describe_index

Get detailed information about a specific index.

Args:

indexName: The name of the index

Returns the index configuration including name, dimension, metric, host, spec, and status.

{
  "type": "object",
  "required": [
    "indexName"
  ],
  "properties": {
    "indexName": {
      "type": "string",
      "description": "Index name"
    }
  }
}

pinecone_delete_index

Delete a Pinecone index.

Args:

indexName: The name of the index to delete

WARNING: This operation is irreversible. All data in the index will be permanently deleted.

{
  "type": "object",
  "required": [
    "indexName"
  ],
  "properties": {
    "indexName": {
      "type": "string",
      "description": "Index name to delete"
    }
  }
}

pinecone_configure_index

Update the configuration of an existing index.

Args:

indexName: The name of the index to configure
replicas: Number of replicas (pod-based indexes only)
podType: Pod type (pod-based indexes only)
deletionProtection: Enable or disable deletion protection
tags: Custom tags to set

Returns the updated index configuration.

{
  "type": "object",
  "required": [
    "indexName"
  ],
  "properties": {
    "tags": {
      "type": "object",
      "description": "Custom tags"
    },
    "podType": {
      "type": "string",
      "description": "Pod type"
    },
    "replicas": {
      "type": "integer",
      "minimum": 1,
      "description": "Number of replicas"
    },
    "indexName": {
      "type": "string",
      "description": "Index name"
    }
  }
}

pinecone_describe_index_stats

Get statistics about an index.

Args:

indexName: The name of the index
filter: Optional metadata filter to get stats for matching vectors only

Returns dimension, total vector count, index fullness, and per-namespace statistics.

{
  "type": "object",
  "required": [
    "indexName"
  ],
  "properties": {
    "filter": {
      "type": "object",
      "description": "Metadata filter"
    },
    "indexName": {
      "type": "string",
      "description": "Index name"
    }
  }
}

pinecone_generate_embeddings

Generate vector embeddings for text inputs.

Args:

model: The embedding model to use (e.g., 'multilingual-e5-large', 'llama-text-embed-v2')
inputs: Array of text strings to embed
inputType: Optional - 'query' or 'passage' for asymmetric models
truncate: How to handle long inputs - 'END' (truncate) or 'NONE' (error)

Returns embeddings (arrays of numbers) for each input.

{
  "type": "object",
  "required": [
    "model",
    "inputs"
  ],
  "properties": {
    "model": {
      "type": "string",
      "description": "Embedding model name"
    },
    "inputs": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Text inputs to embed"
    },
    "truncate": {
      "enum": [
        "END",
        "NONE"
      ],
      "type": "string",
      "default": "END",
      "description": "Truncation handling"
    },
    "inputType": {
      "enum": [
        "query",
        "passage"
      ],
      "type": "string",
      "description": "Input type for asymmetric models"
    }
  }
}

pinecone_rerank_documents

Rerank documents by relevance to a query.

Args:

model: The reranking model to use (e.g., 'bge-reranker-v2-m3')
query: The query to rank documents against
documents: Array of document objects to rerank
topN: Number of top results to return (default: all)
returnDocuments: Include document content in response (default: true)
rankFields: Fields to consider for ranking (default: ['text'])

Returns documents sorted by relevance score.

{
  "type": "object",
  "required": [
    "model",
    "query"
  ],
  "properties": {
    "topN": {
      "type": "integer",
      "minimum": 1,
      "description": "Number of top results"
    },
    "model": {
      "type": "string",
      "description": "Reranking model name"
    },
    "query": {
      "type": "string",
      "description": "Query text"
    },
    "rankFields": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Fields to rank by"
    },
    "returnDocuments": {
      "type": "boolean",
      "default": true,
      "description": "Include documents in response"
    }
  }
}

pinecone_list_models

List available inference models.

Returns information about available embedding and reranking models.

{
  "type": "object",
  "properties": {}
}

pinecone_describe_model

Get detailed information about a specific model.

Args:

modelName: The name of the model

Returns model details including supported parameters and configuration.

{
  "type": "object",
  "required": [
    "modelName"
  ],
  "properties": {
    "modelName": {
      "type": "string",
      "description": "Model name"
    }
  }
}

pinecone_list_namespaces

List all namespaces in an index.

Args:

indexName: The name of the index

Returns an array of namespaces with their vector counts.

{
  "type": "object",
  "required": [
    "indexName"
  ],
  "properties": {
    "indexName": {
      "type": "string",
      "description": "Index name"
    }
  }
}

pinecone_describe_namespace

Get information about a specific namespace.

Args:

indexName: The name of the index
namespaceName: The name of the namespace

Returns the namespace details including vector count.

{
  "type": "object",
  "required": [
    "indexName",
    "namespaceName"
  ],
  "properties": {
    "indexName": {
      "type": "string",
      "description": "Index name"
    },
    "namespaceName": {
      "type": "string",
      "description": "Namespace name"
    }
  }
}

pinecone_delete_namespace

Delete a namespace and all its vectors.

Args:

indexName: The name of the index
namespaceName: The name of the namespace to delete

WARNING: This will delete all vectors in the namespace.

{
  "type": "object",
  "required": [
    "indexName",
    "namespaceName"
  ],
  "properties": {
    "indexName": {
      "type": "string",
      "description": "Index name"
    },
    "namespaceName": {
      "type": "string",
      "description": "Namespace name to delete"
    }
  }
}

pinecone_upsert_vectors

Upsert vectors into an index.

Args:

indexName: The name of the index
vectors: Array of vectors, each with id, values, and optional metadata
namespace: Optional namespace to upsert into

Each vector should have:

id: Unique identifier (string)
values: Array of numbers (must match index dimension)
metadata: Optional key-value pairs

Returns the count of upserted vectors.

{
  "type": "object",
  "required": [
    "indexName"
  ],
  "properties": {
    "indexName": {
      "type": "string",
      "description": "Index name"
    },
    "namespace": {
      "type": "string",
      "description": "Target namespace"
    }
  }
}

pinecone_query_vectors

Query an index for similar vectors.

Args:

indexName: The name of the index
vector: Query vector (array of numbers)
topK: Number of results to return (1-10000)
namespace: Optional namespace to query
filter: Optional metadata filter
includeValues: Include vector values in response
includeMetadata: Include metadata in response
id: Alternative to vector - query by existing vector ID

Returns matched vectors with scores.

{
  "type": "object",
  "required": [
    "indexName",
    "topK"
  ],
  "properties": {
    "id": {
      "type": "string",
      "description": "Query by vector ID instead of vector values"
    },
    "topK": {
      "type": "integer",
      "maximum": 10000,
      "minimum": 1,
      "description": "Number of results"
    },
    "filter": {
      "type": "object",
      "description": "Metadata filter"
    },
    "vector": {
      "type": "array",
      "items": {
        "type": "number"
      },
      "description": "Query vector"
    },
    "indexName": {
      "type": "string",
      "description": "Index name"
    },
    "namespace": {
      "type": "string",
      "description": "Namespace to query"
    },
    "includeValues": {
      "type": "boolean",
      "default": false,
      "description": "Include vector values"
    },
    "includeMetadata": {
      "type": "boolean",
      "default": true,
      "description": "Include metadata"
    }
  }
}

pinecone_fetch_vectors

Fetch vectors by their IDs.

Args:

indexName: The name of the index
ids: Array of vector IDs to fetch
namespace: Optional namespace

Returns the requested vectors with their values and metadata.

{
  "type": "object",
  "required": [
    "indexName",
    "ids"
  ],
  "properties": {
    "ids": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Vector IDs to fetch"
    },
    "indexName": {
      "type": "string",
      "description": "Index name"
    },
    "namespace": {
      "type": "string",
      "description": "Namespace"
    }
  }
}

pinecone_update_vector

Update a vector's values or metadata.

Args:

indexName: The name of the index
id: The vector ID to update
values: New vector values (optional)
setMetadata: Metadata to set or update (optional)
namespace: Optional namespace

At least one of values or setMetadata must be provided.

{
  "type": "object",
  "required": [
    "indexName",
    "id"
  ],
  "properties": {
    "id": {
      "type": "string",
      "description": "Vector ID"
    },
    "values": {
      "type": "array",
      "items": {
        "type": "number"
      },
      "description": "New vector values"
    },
    "indexName": {
      "type": "string",
      "description": "Index name"
    },
    "namespace": {
      "type": "string",
      "description": "Namespace"
    },
    "setMetadata": {
      "type": "object",
      "description": "Metadata to set"
    }
  }
}

pinecone_delete_vectors

Delete vectors from an index.

Args:

indexName: The name of the index
ids: Array of vector IDs to delete (max 1000)
deleteAll: Delete all vectors in the namespace
filter: Delete vectors matching this metadata filter
namespace: Optional namespace

Provide one of: ids, deleteAll, or filter.

{
  "type": "object",
  "required": [
    "indexName"
  ],
  "properties": {
    "ids": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Vector IDs to delete"
    },
    "filter": {
      "type": "object",
      "description": "Metadata filter"
    },
    "deleteAll": {
      "type": "boolean",
      "description": "Delete all vectors"
    },
    "indexName": {
      "type": "string",
      "description": "Index name"
    },
    "namespace": {
      "type": "string",
      "description": "Namespace"
    }
  }
}

pinecone_list_vector_ids

List vector IDs in an index (serverless indexes only).

Args:

indexName: The name of the index
namespace: Optional namespace
prefix: Optional ID prefix to filter by
limit: Maximum number of IDs to return (default 100)
paginationToken: Token for pagination

Returns a list of vector IDs and pagination info.

{
  "type": "object",
  "required": [
    "indexName"
  ],
  "properties": {
    "limit": {
      "type": "integer",
      "default": 100,
      "maximum": 100,
      "minimum": 1,
      "description": "Max results"
    },
    "prefix": {
      "type": "string",
      "description": "ID prefix filter"
    },
    "indexName": {
      "type": "string",
      "description": "Index name"
    },
    "namespace": {
      "type": "string",
      "description": "Namespace"
    },
    "paginationToken": {
      "type": "string",
      "description": "Pagination token"
    }
  }
}