This MCP server is designed for developers to integrate Pinecone with AI coding assistants. It offers a rich toolset covering documentation search, index management, data operations, and advanced search capabilities. Installation is straightforward, supporting Cursor, Claude Desktop, and Gemini CLI. However, it is limited to indexes with integrated inference; those needing other features should consider alternatives.
The Pinecone Developer MCP Server enables AI assistants like Cursor, Claude Desktop, and Gemini CLI to interact with Pinecone projects and documentation. It supports searching documentation, managing indexes, performing data upserts and searches with integrated inference, and executing cross-index searches and reranking. The server is focused on improving the experience of developers working with Pinecone as part of their tech stack.
Generate a Pinecone API key (from console). Ensure Node.js v18 or later is installed and that node and npx are in your PATH.
Configure Cursor: Create a .cursor/mcp.json file in the project root with the configuration (see install_config). Check status in Cursor Settings > MCP.
Configure Claude Desktop: Locate claude_desktop_config.json via Settings > Developer > Edit Config, add the configuration, then restart.
Use as a Gemini CLI extension: Run gemini extensions install https://github.com/pinecone-io/pinecone-mcp and set the PINECONE_API_KEY environment variable.
{
"mcpServers": {
"pinecone": {
"command": "npx",
"args": [
"-y",
"@pinecone-database/mcp"
],
"env": {
"PINECONE_API_KEY": "<your pinecone api key>"
}
}
}
}