Features
- Built-in skills for index management, semantic search, full-text search, assistant creation, and more
- Bundled MCP server (
@pinecone-database/mcp) for direct Pinecone operations from Cursor Agent - Slash commands like
/pinecone-quickstartand/pinecone-queryfor quick access - Natural language activation β Cursor Agent invokes the right skill automatically based on your conversation
Prerequisites
- A Pinecone API key
- Cursor installed
- Node.js v18+ (required for the bundled MCP server)
- uv installed (optional, runs bundled Python scripts)
- Pinecone CLI installed (optional, enables the
pinecone-cliskill)
Installation
1
Set your API key
Add your Pinecone API key to a Cursor loads this file into the MCP server via its
.env file at your workspace root:envFile field, so you donβt need to export the key in your shell.2
Install the plugin
3
Verify the installation
Open Cursor Agent chat and run
/pinecone-help to confirm the skills are loaded. You can also check:- Skills: Cursor Settings > Rules β listed under βAgent Decidesβ
- MCP server: Cursor Settings > Features > Model Context Protocol
Available skills
MCP tools
The plugin includes the Pinecone MCP server, which provides the following tools:search-docsβ Search the official Pinecone documentation.list-indexesβ List all available Pinecone indexes.describe-indexβ Get index configuration and namespaces.describe-index-statsβ Get record counts and namespace statistics.create-index-for-modelβ Create a new index with integrated embeddings.upsert-recordsβ Insert or update records in an index.search-recordsβ Search records with optional metadata filtering and reranking.cascading-searchβ Search across multiple indexes with deduplication and reranking.rerank-documentsβ Rerank documents using a specified reranking model.