How do I install the Pinecone skill?

Run npx skillmds@latest add dvcrn/pinecone in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Pinecone safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: executes scripts, makes network calls, reads secrets. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Pinecone?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Pinecone free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Pinecone?

dvcrn (@dvcrn) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Pinecone by dvcrn — Agent Skill

Name: Pinecone
Rating: 4.2 (5 reviews)
Author: dvcrn

Pinecone

Pinecone vector database — manage indexes, upsert vectors, query similarity search, manage namespaces, and track collections via the Pinecone API. Build semantic search, recommendation systems, and RAG pipelines with high-performance vector storage. Built for AI agents — Python stdlib only, zero dependencies. Use for vector search, semantic similarity, RAG applications, recommendation engines, and AI memory systems.

dvcrn Updated Sep 8, 2026 32 repo stars

File contents

🌲 Pinecone

Pinecone vector database — manage indexes, upsert vectors, query similarity search, manage namespaces, and track collections via the Pinecone API.

Features

Index management — create, configure, delete indexes
Vector upsert — insert and update vectors with metadata
Similarity search — query nearest neighbors
Namespace management — organize vectors by namespace
Metadata filtering — filter queries by metadata fields
Collection management — create snapshots of indexes
Batch operations — bulk upsert and delete
Index stats — vector counts, dimensions, usage
Sparse-dense — hybrid search with sparse vectors
Serverless — auto-scaling serverless indexes

Requirements

Variable	Required	Description
`PINECONE_API_KEY`	✅	API key/token for Pinecone

Quick Start

# List indexes
python3 {baseDir}/scripts/pinecone.py indexes

# Get index details
python3 {baseDir}/scripts/pinecone.py index-get my-index

# Create an index
python3 {baseDir}/scripts/pinecone.py index-create '{"name":"my-index","dimension":1536,"metric":"cosine","spec":{"serverless":{"cloud":"aws","region":"us-east-1"}}}'

# Delete an index
python3 {baseDir}/scripts/pinecone.py index-delete my-index

Commands

`indexes`

List indexes.

python3 {baseDir}/scripts/pinecone.py indexes

`index-get`

Get index details.

python3 {baseDir}/scripts/pinecone.py index-get my-index

`index-create`

Create an index.

python3 {baseDir}/scripts/pinecone.py index-create '{"name":"my-index","dimension":1536,"metric":"cosine","spec":{"serverless":{"cloud":"aws","region":"us-east-1"}}}'

`index-delete`

Delete an index.

python3 {baseDir}/scripts/pinecone.py index-delete my-index

`upsert`

Upsert vectors.

python3 {baseDir}/scripts/pinecone.py upsert --index my-index '{"vectors":[{"id":"vec1","values":[0.1,0.2,...],"metadata":{"text":"hello"}}]}'

`query`

Query similar vectors.

python3 {baseDir}/scripts/pinecone.py query --index my-index '{"vector":[0.1,0.2,...],"topK":10,"includeMetadata":true}'

`fetch`

Fetch vectors by ID.

python3 {baseDir}/scripts/pinecone.py fetch --index my-index --ids vec1,vec2,vec3

`delete`

Delete vectors.

python3 {baseDir}/scripts/pinecone.py delete --index my-index --ids vec1,vec2

`delete-namespace`

Delete all vectors in namespace.

python3 {baseDir}/scripts/pinecone.py delete-namespace --index my-index --namespace docs

`stats`

Get index statistics.

python3 {baseDir}/scripts/pinecone.py stats --index my-index

`collections`

List collections.

python3 {baseDir}/scripts/pinecone.py collections

`collection-create`

Create collection from index.

python3 {baseDir}/scripts/pinecone.py collection-create '{"name":"backup","source":"my-index"}'

`namespaces`

List namespaces in index.

python3 {baseDir}/scripts/pinecone.py namespaces --index my-index

Output Format

All commands output JSON by default. Add --human for readable formatted output.

# JSON (default, for programmatic use)
python3 {baseDir}/scripts/pinecone.py indexes --limit 5

# Human-readable
python3 {baseDir}/scripts/pinecone.py indexes --limit 5 --human

Script Reference

Script	Description
`{baseDir}/scripts/pinecone.py`	Main CLI — all Pinecone operations

Data Policy

This skill never stores data locally. All requests go directly to the Pinecone API and results are returned to stdout. Your data stays on Pinecone servers.

Credits

Built by M. Abidi | agxntsix.ai YouTube | GitHub Part of the AgxntSix Skill Suite for OpenClaw agents.

📅 Need help setting up OpenClaw for your business? Book a free consultation

---name: pineconedescription: Pinecone vector database — manage indexes, upsert vectors, query similarity search, manage namespaces, and track collections via the Pinecone API. Build semantic search, recommendation systems, and RAG pipelines with high-performance vector storage. Built for AI agents — Python stdlib only, zero dependencies. Use for vector search, semantic similarity, RAG applications, recommendation engines, and AI memory systems.---# 🌲 PineconePinecone vector database — manage indexes, upsert vectors, query similarity search, manage namespaces, and track collections via the Pinecone API.## Features- **Index management** — create, configure, delete indexes- **Vector upsert** — insert and update vectors with metadata- **Similarity search** — query nearest neighbors- **Namespace management** — organize vectors by namespace- **Metadata filtering** — filter queries by metadata fields- **Collection management** — create snapshots of indexes- **Batch operations** — bulk upsert and delete- **Index stats** — vector counts, dimensions, usage- **Sparse-dense** — hybrid search with sparse vectors- **Serverless** — auto-scaling serverless indexes## Requirements| Variable | Required | Description ||----------|----------|-------------|| `PINECONE_API_KEY` | ✅ | API key/token for Pinecone |## Quick Start```bash# List indexespython3 {baseDir}/scripts/pinecone.py indexes``````bash# Get index detailspython3 {baseDir}/scripts/pinecone.py index-get my-index``````bash# Create an indexpython3 {baseDir}/scripts/pinecone.py index-create '{"name":"my-index","dimension":1536,"metric":"cosine","spec":{"serverless":{"cloud":"aws","region":"us-east-1"}}}'``````bash# Delete an indexpython3 {baseDir}/scripts/pinecone.py index-delete my-index```## Commands### `indexes`List indexes.```bashpython3 {baseDir}/scripts/pinecone.py indexes```### `index-get`Get index details.```bashpython3 {baseDir}/scripts/pinecone.py index-get my-index```### `index-create`Create an index.```bashpython3 {baseDir}/scripts/pinecone.py index-create '{"name":"my-index","dimension":1536,"metric":"cosine","spec":{"serverless":{"cloud":"aws","region":"us-east-1"}}}'```### `index-delete`Delete an index.```bashpython3 {baseDir}/scripts/pinecone.py index-delete my-index```### `upsert`Upsert vectors.```bashpython3 {baseDir}/scripts/pinecone.py upsert --index my-index '{"vectors":[{"id":"vec1","values":[0.1,0.2,...],"metadata":{"text":"hello"}}]}'```### `query`Query similar vectors.```bashpython3 {baseDir}/scripts/pinecone.py query --index my-index '{"vector":[0.1,0.2,...],"topK":10,"includeMetadata":true}'```### `fetch`Fetch vectors by ID.```bashpython3 {baseDir}/scripts/pinecone.py fetch --index my-index --ids vec1,vec2,vec3```### `delete`Delete vectors.```bashpython3 {baseDir}/scripts/pinecone.py delete --index my-index --ids vec1,vec2```### `delete-namespace`Delete all vectors in namespace.```bashpython3 {baseDir}/scripts/pinecone.py delete-namespace --index my-index --namespace docs```### `stats`Get index statistics.```bashpython3 {baseDir}/scripts/pinecone.py stats --index my-index```### `collections`List collections.```bashpython3 {baseDir}/scripts/pinecone.py collections```### `collection-create`Create collection from index.```bashpython3 {baseDir}/scripts/pinecone.py collection-create '{"name":"backup","source":"my-index"}'```### `namespaces`List namespaces in index.```bashpython3 {baseDir}/scripts/pinecone.py namespaces --index my-index```## Output FormatAll commands output JSON by default. Add `--human` for readable formatted output.```bash# JSON (default, for programmatic use)python3 {baseDir}/scripts/pinecone.py indexes --limit 5# Human-readablepython3 {baseDir}/scripts/pinecone.py indexes --limit 5 --human```## Script Reference| Script | Description ||--------|-------------|| `{baseDir}/scripts/pinecone.py` | Main CLI — all Pinecone operations |## Data PolicyThis skill **never stores data locally**. All requests go directly to the Pinecone API and results are returned to stdout. Your data stays on Pinecone servers.## Credits---Built by [M. Abidi](https://www.linkedin.com/in/mohammad-ali-abidi) | [agxntsix.ai](https://www.agxntsix.ai)[YouTube](https://youtube.com/@aiwithabidi) | [GitHub](https://github.com/aiwithabidi)Part of the **AgxntSix Skill Suite** for OpenClaw agents.📅 **Need help setting up OpenClaw for your business?** [Book a free consultation](https://cal.com/agxntsix/abidi-openclaw)

Frequently asked questions

Pinecone

File contents

🌲 Pinecone

Features

Requirements

Quick Start

Commands

indexes

index-get

index-create

index-delete

upsert

query

fetch

delete

delete-namespace

stats

collections

collection-create

namespaces