pinecone-io/skills

pinecone-help

Overview of all available Pinecone skills and what a user needs to get started.

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원본 Skill 문서

원본 저장소의 제목, 예시, 코드, 표, 링크, 이미지를 유지해 표시합니다.

Pinecone Skills — Help & Overview

Pinecone is the leading vector database for building accurate and performant AI applications at scale in production. It's useful for building semantic search, retrieval augmented generation, recommendation systems, and agentic applications.

Here's everything you need to get started and a summary of all available skills.

<<invokeanyskill>>


What You Need

Required

  • Pinecone account — free to create at https://app.pinecone.io/?sessionType=signup
  • API key — create one in the Pinecone console after signing up, then make it

available to this environment: <<apikeysetup>>

Optional (unlock more capabilities)

ToolWhat it enablesInstall
Pinecone MCP serverUse Pinecone directly inside your AI agent/IDE without writing codeSetup guide
Pinecone CLI (`pc`)Manage all index types from the terminal, batch operations, backups, CI/CDbrew tap pinecone-io/tap && brew install pinecone-io/tap/pinecone
uvRun the packaged Python scripts included in these skillsInstall uv

Available Skills

SkillWhat it does
pinecone-quickstartStep-by-step onboarding — create an index, upload data, and run your first search
pinecone-querySearch integrated indexes using natural language text via the Pinecone MCP
pinecone-cliUse the Pinecone CLI (pc) for terminal-based index and vector management
pinecone-assistantCreate, manage, and chat with Pinecone Assistants for document Q&A with citations
pinecone-mcpReference for all Pinecone MCP server tools and their parameters
pinecone-full-text-searchBuild a full-text-search index — schema design, safe bulk ingestion, and query construction (text / query_string / dense / sparse scoring with text-match and metadata filters). Document-schema API (`2026-07`); requires `pinecone` Python SDK ≥ 10.0.0.
pinecone-docsCurated links to official Pinecone documentation, organized by topic
pinecone-n8nBuild n8n workflows with the Pinecone Assistant node or Pinecone Vector Store node, including best practices and full workflow JSON generation

Which skill should I use?

Just getting started?pinecone-quickstart

Want to search an index you already have?

  • Integrated index (built-in embedding model) → pinecone-query (uses MCP)
  • Any other index type → pinecone-cli

Working with documents and Q&A?pinecone-assistant

Building a full-text search index (BM25-style keyword/phrase matching, optionally combined with dense or sparse vectors)?pinecone-full-text-search (document-schema API, needs pinecone Python SDK ≥ 10.0.0)

Building an n8n workflow with Pinecone (RAG pipeline, chat with docs)?pinecone-n8n

Need to manage indexes, bulk upload vectors, or automate workflows?pinecone-cli

Looking up API parameters or SDK usage?pinecone-docs

Need to understand what MCP tools are available?pinecone-mcp

같은 저장소의 Skills

더 많은 Skills

모든 Skills
pinecone-io
공식

pinecone-assistant

Create, manage, and chat with Pinecone Assistants for document Q&A with citations. Handles all assistant operations - create, upload, sync, chat, context retrieval, and list. Recognizes natural language like "create an assistant from my docs", "ask my assistant about X", or "upload my docs to Pinecone".

설치 수
2
GitHub Stars
15
업데이트
9월 9일
pinecone-io
공식

pinecone-cli

Guide for using the Pinecone CLI (pc) to manage Pinecone resources from the terminal. The CLI supports ALL index types (standard, integrated, sparse) and all vector operations — unlike the MCP which only supports integrated indexes. Use for batch operations, vector management, backups, namespaces, CI/CD automation, and full control over Pinecone resources.

설치 수
2
GitHub Stars
15
업데이트
9월 9일
pinecone-io
공식

pinecone-docs

Curated documentation reference for developers building with Pinecone. Contains links to official docs organized by topic and data format references. Use when writing Pinecone code, looking up API parameters, or needing the correct format for vectors or records.

설치 수
2
GitHub Stars
15
업데이트
9월 9일
pinecone-io
공식

pinecone-full-text-search

Create, ingest into, and query a Pinecone full-text-search (FTS) document index using the graduated document-schema API (Python SDK 10.0.0, API version 2026-07). Use when the user or agent asks to build a text search index on Pinecone, add dense or sparse vector fields, ingest documents, construct scoreby clauses (text / querystring / densevector / sparsevector), or compose with text-match filters ($matchphrase / $matchall / $matchany). Ships scripts/ingest.py for safe bulk ingestion (batchupsert + error inspection + readiness polling); query construction is documented inline in this skill — write documents.search(...) calls directly, validated against pc.indexes.describe(...) output.

설치 수
2
GitHub Stars
15
업데이트
9월 9일