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pinecone Plugin

Category
Database
Topics
Databases & Storage · AI Agents & AI App Development
First seen
2026-07-09
Last confirmed
2026-07-13
Explanation last updated
2026-07-12

The explanation below is AI-generated. Please verify it against the sources.

This is the official Pinecone plugin for Claude Code, which integrates Pinecone vector database capabilities directly into Claude Code for semantic search, index management, and RAG workflows. It provides slash-command skills such as /pinecone:quickstart, /pinecone:query, /pinecone:full-text-search, and /pinecone:assistant, plus access to the full Pinecone MCP Server for creating, listing, searching, and upserting indexes. Installation is done via the Claude Code Plugins Directory or the Pinecone marketplace, and requires a PINECONE_API_KEY; assistant-related commands additionally require the uv Python package manager, and the CLI installation is optional. According to the README, the /pinecone:query command only works with integrated indexes that use Pinecone's hosted embedding models. The project is MIT licensed and maintained by pinecone-io on GitHub.

Overview

Pinecone is a vector database used for semantic search, RAG (Retrieval Augmented Generation), and related vector-based applications; this plugin connects Claude Code to Pinecone's MCP server and Assistant service, per the README.

What you can do with pinecone

  • Run /pinecone:quickstart to create an integrated index, upsert data, and query it using Pinecone MCP + Python, or to set up a Pinecone Assistant
  • Use /pinecone:query to search integrated indexes with natural language (works only with Pinecone's hosted embedding models)
  • Use /pinecone:full-text-search for the FTS preview API (2026-01.alpha), covering BM25, dense/sparse vector scoring, and text-match filters, including a scripts/ingest.py helper for bulk upsert with error inspection
  • Use /pinecone:assistant to create, upload to, sync, chat with, and retrieve context from a Pinecone Assistant, via slash commands or natural language
  • Use /pinecone:cli and /pinecone:mcp for guidance on the Pinecone CLI (pc) and the full list of MCP server tools (list-indexes, describe-index, describe-index-stats, search-records, create-index-for-model, upsert-records, rerank-documents)
  • Use /pinecone:docs and /pinecone:help for curated documentation links and a skills overview

Sources

Original description (English)

Pinecone vector database integration. Streamline your Pinecone development with powerful tools for managing vector indexes, querying data, and rapid prototyping. Use slash commands like /quickstart to generate AGENTS.md files and initialize Python projects and /query to quickly explore indexes. Access the Pinecone MCP server for creating, describing, upserting and querying indexes with Claude. Perfect for developers building semantic search, RAG applications, recommendation systems, and other vector-based applications with Pinecone.

History of pinecone

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