Pinecone Developer MCP Server
Databasestdio
Pinecone's official MCP server connects AI assistants to Pinecone vector databases for retrieval-augmented generation (RAG) workflows. Lets agents create and configure indexes, upsert and embed documents, and run semantic searches over vector data — all from natural language, without leaving the editor or chat.
Connect
Add this configuration to .claude/mcp.json
{
"mcpServers": {
"pinecone": {
"command": "npx",
"args": [
"-y",
"@pinecone-database/mcp"
],
"env": {
"PINECONE_API_KEY": "<YOUR_PINECONE_API_KEY>"
}
}
}
}Tools (2)
search-records
Run a semantic search over a Pinecone index and return the most relevant records.
{
"type": "object",
"required": [
"index_name",
"query"
],
"properties": {
"query": {
"type": "string",
"description": "Natural-language query to search for"
},
"top_k": {
"type": "integer",
"description": "Number of results to return"
},
"index_name": {
"type": "string",
"description": "Name of the Pinecone index to query"
}
}
}upsert-records
Insert or update records (with text to embed) into a Pinecone index.
{
"type": "object",
"required": [
"index_name",
"records"
],
"properties": {
"records": {
"type": "array",
"items": {
"type": "object"
},
"description": "Records to upsert, each with an id and text/metadata"
},
"index_name": {
"type": "string",
"description": "Name of the target Pinecone index"
}
}
}Resources
This server does not expose any resources.
Prompts
This server does not expose any prompts.
Server Information
- Author
- Pinecone (@pinecone-io)
- License
- MIT
- Stars
- 0
- Last Updated
- June 12, 2026