Pinecone is a Databases MCP server that lets Claude Code, Cursor, Windsurf and any MCP-compatible AI agent vector database for AI embeddings. Install in 1 minute with mcpizy install pinecone.
Databases
Vector database for AI embeddings
Official homepagemcpizy install pineconenpx -y pinecone-mcplist_indexesList all Pinecone indexes
create_indexCreate a new index
Inputs
namestringrequireddimensionnumberrequiredmetricstringoptionalupsert_vectorsInsert or update vectors into an index
Inputs
index_namestringrequiredvectorsobject[]requiredquery_vectorsQuery nearest vectors to an input
Inputs
index_namestringrequiredvectornumber[]requiredtop_knumberoptionaldelete_vectorsDelete vectors by ID
Inputs
index_namestringrequiredidsstring[]requiredWorks identically across clients. Only the config file path differs.
~/.claude.json{
"mcpServers": {
"pinecone": {
"command": "npx",
"args": [
"-y",
"@pinecone-database/mcp"
],
"env": {
"PINECONE_API_KEY": "..."
}
}
}
}.cursor/mcp.json{
"mcpServers": {
"pinecone": {
"command": "npx",
"args": [
"-y",
"@pinecone-database/mcp"
],
"env": {
"PINECONE_API_KEY": "..."
}
}
}
}~/.codeium/windsurf/mcp_config.json{
"mcpServers": {
"pinecone": {
"command": "npx",
"args": [
"-y",
"@pinecone-database/mcp"
],
"env": {
"PINECONE_API_KEY": "..."
}
}
}
}Copy your API key from the Pinecone console
PINECONE_API_KEYPaste any of these prompts into Claude Code, Cursor or another MCP-compatible client.
“List every index I have and their dimension”
Uses: list_indexes
“Create a 1536-dim index named 'docs' for OpenAI embeddings”
Uses: create_index
“Find the 5 most similar vectors to this embedding in my 'docs' index”
Uses: query_vectors
If Pinecone doesn't fit your stack, these Databases MCP servers solve similar problems.
The Pinecone MCP server is an Databases Model Context Protocol server that lets Claude Code, Cursor, Windsurf, VS Code with Copilot, and other MCP-compatible AI agents vector database for AI embeddings. It exposes Pinecone's capabilities as tools the AI can call directly from your editor or CLI.
The fastest way is the MCPizy CLI: run `mcpizy install pinecone` and MCPizy will add the server to your `.claude.json` automatically. You can also install it manually by adding an entry under `mcpServers` in `.claude.json` with the command `npx -y pinecone-mcp` and restarting Claude Code.
Yes. The Pinecone MCP server is free and open source. You may still need a Pinecone account or API key to connect the server to the underlying service, but the MCP layer itself has no MCPizy subscription cost.
Yes. Any MCP-compatible client works — including Claude Code, Claude Desktop, Cursor (via `.cursor/mcp.json`), Windsurf, VS Code with Copilot Chat, and custom agents built on the MCP SDK. The same install command targets all of them; only the config file path differs.
Once installed, your AI agent can vector database for AI embeddings directly inside your conversation. Typical use cases include asking Claude Code or Cursor to run Pinecone operations, inspect results, chain Pinecone with other MCP servers (see our Workflow Recipes), and automate repetitive databases tasks without leaving your editor.