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The Stack · Vector DB & data infra API

Pinecone

The managed serverless vector database most RAG teams reach for — autoscales to zero, with a control-plane Admin API for programmatic project and key provisioning.

API keyFreemium🟢 agent: programmatic apiMCP ✓
Get API key → agent-provisionable DocsWebsite
CategoryVector DB & data infra
TypeAPI service
Authapi-key
PricingFreemium
Agent signup🟢 programmatic api
SDKsPython, TypeScript, Go, Java, REST
MCP serveravailable →

Pricing: Free Starter (2GB storage, ~2M writes / 1M reads per mo, AWS us-east-1); Builder $20/mo flat; Standard from $50/mo

🟢 Agents: programmatic api

Programmatic — an agent can provision a key end-to-end, no human.

Free Starter signup returns an instant API key (no CC). Admin API: create a service account in console (client_id/secret), exchange for a token, then create projects and scoped API keys programmatically (roles like ProjectEditor). Official developer MCP server.

Pinecone — The managed serverless vector database most RAG teams reach for — autoscales to zero, with a control-plane Admin API for programmatic project and key provisioning.
Website: https://www.pinecone.io
Docs: https://docs.pinecone.io
Get a key: https://app.pinecone.io
Agent signup: programmatic api — Free Starter signup returns an instant API key (no CC). Admin API: create a service account in console (client_id/secret), exchange for a token, then create projects and scoped API keys programmatically (roles like ProjectEditor). Official developer MCP server.
Auth: api-key
MCP server: @pinecone-database/mcp
Pricing: freemium — Free Starter (2GB storage, ~2M writes / 1M reads per mo, AWS us-east-1); Builder $20/mo flat; Standard from $50/mo
Full record: https://dreaming.press/api/tools/pinecone.json

Machine record: /api/tools/pinecone.json · add its MCP server →

Quickstart

from pinecone import Pinecone

pc = Pinecone(api_key="YOUR_API_KEY")
index = pc.Index("my-index")
index.upsert(vectors=[{"id": "a1", "values": [0.1, 0.2, 0.3]}])
res = index.query(vector=[0.1, 0.2, 0.3], top_k=3, include_metadata=True)

python · full docs →

Model Context Protocol

Pinecone exposes an MCP server, so you can add its tools to Claude, Cursor, or any MCP client: @pinecone-database/mcp

Pinecone in our coverage

Pinecone Added Full-Text Search: One Index for BM25 and Vectors Doesn't Mean One Query

Best Vector Database for Multi-Agent Systems: Why the Single-Query Leaderboard Lies

Pinecone Nexus and KnowQL: When Retrieval Becomes a Compile Step

RAG Without a Vector Database: What PageIndex's Reasoning-Based Retrieval Actually Trades

Right to Be Forgotten in RAG: How to Actually Delete a User From a Vector Database

Filesystem vs Vector Database for Agent Memory: Why 2026 Agents Write to Files

Pinecone FAQ

What is Pinecone?

Pinecone is The managed serverless vector database most RAG teams reach for — autoscales to zero, with a control-plane Admin API for programmatic project and key provisioning. It's in the Vector DB & data infra category of the dreaming.press tool directory.

Is Pinecone free?

Pinecone is freemium — free to start, paid plans for scale. Free Starter (2GB storage, ~2M writes / 1M reads per mo, AWS us-east-1); Builder $20/mo flat; Standard from $50/mo.

Can an AI agent sign up for Pinecone automatically?

Yes — an agent can create an account and provision a key end-to-end with no human, via its API or OAuth device flow. Free Starter signup returns an instant API key (no CC). Admin API: create a service account in console (client_id/secret), exchange for a token, then create projects and scoped API keys programmatically (roles like ProjectEditor). Official developer MCP server..

Does Pinecone have an MCP server?

Yes — Pinecone offers a Model Context Protocol server, so you can add its tools to Claude, Cursor, or any MCP client: @pinecone-database/mcp

Is Pinecone open source?

Pinecone is a hosted API service, not an open-source project.

What languages does Pinecone support?

Pinecone offers Python, TypeScript, Go, Java, REST.

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