Pinecone API

by docs.pinecone.io

Embeddings and reranking Added on November 3rd, 2026

What it does

Pinecone is a managed vector database with hosted embedding and reranking models, for semantic search or retrieval-augmented generation (RAG). Requests are JSON over HTTPS with an Api-Key header. Free on the Starter plan: up to 2 GB storage, 1 million read units and 2 million write units a month, 5 million embedding tokens a month per hosted model and 500 rerank requests a month. An official MCP server (npm package @pinecone-database/mcp) lets AI agents search and manage indexes.

API
JSON
MCP
REST

At a glance

API key: Needed, free · More APIs with a free key
Pricing: Free on the Starter plan: up to 2 GB storage, 1 million read units and 2 million write units a month, 5 million embedding tokens a month per hosted model and 500 rerank requests a month.
From the browser: Yes (CORS)
Formats: JSON
Interface: REST, MCP
Provider: docs.pinecone.io

More information: https://docs.pinecone.io/guides/index-data/create-an-index

Compare: Pinecone API vs Qdrant Cloud

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HTML

<a href="https://free-web-services.com/web-services/ai/embeddings/pinecone-api.html"><img src="https://free-web-services.com/badge.svg" width="208" height="44" alt="Listed on Free Web Services" /></a>

Markdown

[![Listed on Free Web Services](https://free-web-services.com/badge.svg)](https://free-web-services.com/web-services/ai/embeddings/pinecone-api.html)

Example request

curl

curl -X POST 'https://api.pinecone.io/embed' \
  -H 'Api-Key: YOUR_API_KEY' \
  -H 'X-Pinecone-Api-Version: 2025-10' \
  -H 'Content-Type: application/json' \
  -d '{"model":"llama-text-embed-v2","parameters":{"input_type":"passage"},"inputs":[{"text":"The quick brown fox"}]}'

JavaScript

const response = await fetch("https://api.pinecone.io/embed", {
  method: 'POST',
  headers: {
    "Api-Key": "YOUR_API_KEY",
    "X-Pinecone-Api-Version": "2025-10",
    "Content-Type": "application/json",
  },
  body: JSON.stringify({"model":"llama-text-embed-v2","parameters":{"input_type":"passage"},"inputs":[{"text":"The quick brown fox"}]}),
});
const data = await response.json();
console.log(data);

Python

import requests

response = requests.post(
    "https://api.pinecone.io/embed",
    headers={
        "Api-Key": "YOUR_API_KEY",
        "X-Pinecone-Api-Version": "2025-10",
        "Content-Type": "application/json",
    },
    json={
        "model": "llama-text-embed-v2",
        "parameters": {
            "input_type": "passage",
        },
        "inputs": [
            {
                "text": "The quick brown fox",
            },
        ],
    },
    timeout=30,
)
print(response.json())

Replace YOUR_API_KEY with your own key. The JavaScript works in a web page as well as in Node.js 18 or newer.