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Pinecone Cursor Plugin

Official Pinecone plugin for Cursor. Build semantic search, RAG, recommendation systems, and other vector-based applications with Pinecone — directly from your editor.

What's included

Skills

Skills are specialized agent capabilities invoked automatically by Cursor Agent or manually via /skill-name in chat.

Skill What it does
/pinecone-quickstart Step-by-step onboarding — create an index, upload data, and run your first search. Choose between a Database path (vector search) or Assistant path (document Q&A).
/pinecone-query Search integrated indexes using natural language text via the Pinecone MCP server.
/pinecone-cli Use the Pinecone CLI (pc) for terminal-based index and vector management.
/pinecone-assistant Create, manage, and chat with Pinecone Assistants for document Q&A with citations. Includes scripts for uploading files, syncing changes, and retrieving context.
/pinecone-full-text-search Create, ingest into, and query a Pinecone full-text-search (FTS) index using the preview API.
/pinecone-mcp Reference documentation for all Pinecone MCP server tools and their parameters.
/pinecone-docs Curated links to official Pinecone documentation, organized by topic.
/pinecone-help Overview of all available skills and what you need to get started.

MCP Server

The plugin bundles the Pinecone MCP server (@pinecone-database/mcp), giving Cursor Agent direct access to your Pinecone resources:

  • Create, describe, and delete indexes
  • Upsert and query vectors
  • Search Pinecone documentation
  • Manage index configurations

Bundled Scripts

Several skills include Python scripts (run via uv) for operations beyond what MCP provides:

Script Skill Purpose
upsert.py pinecone-quickstart Seed an index with sample data
quickstart_complete.py pinecone-quickstart Standalone end-to-end quickstart
create.py pinecone-assistant Create a new Pinecone Assistant
upload.py pinecone-assistant Upload files to an assistant
chat.py pinecone-assistant Chat with an assistant
context.py pinecone-assistant Retrieve context snippets from an assistant
list.py pinecone-assistant List all assistants in your account
sync.py pinecone-assistant Sync local files to an assistant
ingest.py pinecone-full-text-search Bulk-ingest a prepared JSONL into an FTS index

Installation

Run the following command in Cursor chat:

/add-plugin pinecone

Or install directly from the marketplace: cursor.com/marketplace/pinecone

Prerequisites

  • Pinecone account — free at app.pinecone.io
  • API key — create one in the Pinecone console, then add it to a .env file at your workspace root:
    PINECONE_API_KEY=your-key
    
    The bundled MCP config loads this file via Cursor's envFile field, so you don't need to export the key in your shell. (If you prefer, export PINECONE_API_KEY="your-key" also works for terminal scripts.)
  • Node.js v18+ — required for the MCP server (npx)

Optional

Tool What it enables Install
Pinecone CLI (pc) Terminal-based index management, batch operations brew tap pinecone-io/tap && brew install pinecone-io/tap/pinecone
uv Run the bundled Python scripts Install guide

Getting started

  1. Install the plugin from the Cursor Marketplace
  2. Add PINECONE_API_KEY=your-key to a .env file at your workspace root (Cursor will load it into the MCP server via envFile)
  3. Open Cursor Agent chat and type /pinecone-quickstart to get started
  4. Verify the MCP server is connected: Cursor Settings > Features > Model Context Protocol

Verifying the installation

Component Where to check
Skills Cursor Settings > Rules — listed under "Agent Decides"
MCP Server Cursor Settings > Features > Model Context Protocol
Commands Type / in Agent chat and search

Links

License

Apache-2.0

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