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pinecone:cli

Manage Pinecone indexes, vectors, backups, and namespaces from the terminal using the pc CLI.

68|12|Updated Dec 17, 2025
Search Tags:#ci/cd#semantic search#cli#vector database#backup#index management#pinecone
One-click install
npx skills add https://github.com/pinecone-io/pinecone-claude-code-plugin --skill pinecone-cli-pinecone-io
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: pinecone:cli
Source: https://github.com/pinecone-io/pinecone-claude-code-plugin/tree/main/skills/cli
Command: npx skills add https://github.com/pinecone-io/pinecone-claude-code-plugin --skill pinecone-cli-pinecone-io

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? Managing Pinecone vector databases often requires operations the MCP server cannot perform, such as vector upserts, queries with raw embeddings, backups, and namespace management across all index types. This Skill provides complete terminal-based control over Pinecone resources for both interactive work and CI/CD automation. ## Core Features & Use Cases - Full Vector Operations: Upsert, query, fetch, update, and delete vectors on any index type (standard, integrated, sparse), including queries with raw embedding vectors generated externally. - Index & Resource Management: Create, configure, and delete indexes, manage namespaces, organizations, projects, and API keys from the command line. - Backups & Automation: Create and restore index backups, preview destructive updates with dry-run mode, and script workflows using JSON output with jq. - Use Case: Before a production migration, create a backup with pc backup create, bulk-update vector metadata with a dry-run preview, then restore to a new index if anything goes wrong. ## Quick Start Ask the assistant to install the Pinecone CLI, authenticate with pc login, and list all indexes in your current project.

Frequently Asked Questions about pinecone:cli

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I query a Pinecone index with a custom embedding vector?▼

Use pc index vector query with the --vector flag passing your embedding as a JSON array, plus -k for result count and --include-metadata. You can also pipe embeddings from stdin, for example jq -c '.embedding' doc.json | pc index vector query -n my-index --vector - -k 10.

What is the difference between the Pinecone CLI and the Pinecone MCP server?▼

The CLI supports all index types (standard, integrated, sparse) and full vector operations like upsert, query, fetch, update, and delete. The MCP server only supports integrated indexes and text search, lacking vector operations, backups, and namespace management.

How do I authenticate the Pinecone CLI for CI/CD pipelines?▼

Use a service account with pc auth configure --client-id and --client-secret, passing credentials via environment variables. For local development, pc login with pc target is recommended, while pc config set-api-key works for quick testing.

Does pc login set the PINECONE_API_KEY environment variable?▼

No, pc login only authenticates the CLI tool itself and does not set PINECONE_API_KEY. SDKs and scripts need the key set separately, which you can create with pc api-key create and export manually.

Why does my Pinecone vector upsert fail with a dimension mismatch?▼

The upsert fails because your vectors do not match the index's configured dimension. Run pc index describe -n my-index to check the expected dimension and ensure every vector in your file has exactly that many values.

How do I back up and restore a Pinecone serverless index?▼

Run pc backup create -i my-index -n backup-name to snapshot a serverless index in Ready state. Restore with pc backup restore -i <backup-uuid> -n new-index-name, which creates a new index from the backup.

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