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References curated Pinecone documentation links on indexes, upsert, search, metadata filtering, APIs, and SDKs. Use when coding Pinecone integrations or looking up parameters.
How this skill is triggered — by the user, by Claude, or both
Slash command
/pinecone:docsThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
A curated index of Pinecone documentation. Fetch the relevant page(s) for the task at hand rather than relying on training data.
A curated index of Pinecone documentation. Fetch the relevant page(s) for the task at hand rather than relying on training data.
Please attempt to fetch the url listed when relevant. If you run into an error, please attempt to append ".md" to the url to retrieve the markdown version of the Docs page.
In case you need it: A full reference to ALL relevant URLs can be found here: https://docs.pinecone.io/llms.txt
Use this as a last resort if you cannot find the relevant page below.
| Topic | URL |
|---|---|
| Quickstart for all languages and coding environments (Cursor, Claude Code, n8n, Python, JavaScript, Java, Go, C#) | https://docs.pinecone.io/guides/get-started/quickstart |
| Pinecone concepts — namespaces, terminology, and key database concepts | https://docs.pinecone.io/guides/get-started/concepts |
| Data modeling for text and vectors | https://docs.pinecone.io/guides/index-data/data-modeling |
| Architecture of Pinecone | https://docs.pinecone.io/guides/get-started/database-architecture |
| Pinecone Assistant overview | https://docs.pinecone.io/guides/assistant/overview |
| Topic | URL |
|---|---|
| Create an index | https://docs.pinecone.io/guides/index-data/create-an-index |
| Index types and conceptual overview | https://docs.pinecone.io/guides/index-data/indexing-overview |
| Integrated inference (built-in embedding models) | https://docs.pinecone.io/guides/index-data/indexing-overview#integrated-embedding |
| Dedicated read nodes — predictable low-latency performance at high query volumes | https://docs.pinecone.io/guides/index-data/dedicated-read-nodes |
| Topic | URL |
|---|---|
| Upsert vectors and text | https://docs.pinecone.io/guides/index-data/upsert-data |
| Multitenancy with namespaces | https://docs.pinecone.io/guides/index-data/implement-multitenancy |
| Topic | URL |
|---|---|
| Semantic search | https://docs.pinecone.io/guides/search/semantic-search |
| Hybrid search | https://docs.pinecone.io/guides/search/hybrid-search |
| Lexical search | https://docs.pinecone.io/guides/search/lexical-search |
Full-text search (preview) — document-schema FTS indexes with text / query_string / dense / sparse scoring | https://docs.pinecone.io/guides/search/full-text-search |
| Metadata filtering — narrow results and speed up searches | https://docs.pinecone.io/guides/search/filter-by-metadata |
| Topic | URL |
|---|---|
| Python SDK reference | https://docs.pinecone.io/reference/sdks/python/overview |
| Example Colab notebooks | https://docs.pinecone.io/examples/notebooks |
| Topic | URL |
|---|---|
| Production checklist — preparing your index for production | https://docs.pinecone.io/guides/production/production-checklist |
| Common errors and what they mean | https://docs.pinecone.io/guides/production/error-handling |
| Targeting indexes correctly — don't use index names in prod | https://docs.pinecone.io/guides/manage-data/target-an-index#target-by-index-host-recommended |
See references/data-formats.md for vector and record schemas.
npx claudepluginhub pinecone-io/pinecone-claude-code-plugin --plugin pineconeLists all available Pinecone skills, activation triggers, and setup requirements including API key, MCP server, CLI, and uv.
Provides patterns and Python templates for similarity search with vector databases, including metrics, indexes, and Pinecone implementation. Use for semantic search, RAG, recommendations, and scaling.
Guides vector database selection for embeddings and semantic search, compares managed options like Pinecone and self-hosted like pgvector/Milvus, explains ANN algorithms like HNSW.