Query integrated indexes using text with Pinecone MCP. IMPORTANT - This skill ONLY works with integrated indexes (indexes with built-in Pinecone embedding models like multilingual-e5-large). For standard indexes or…
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name: pinecone-query
description: Query integrated indexes using text with Pinecone MCP. IMPORTANT - This skill ONLY works with integrated indexes (indexes with built-in Pinecone embedding models like multilingual-e5-large). For standard indexes or advanced vector operations, use the CLI skill instead. Requires PINECONE_API_KEY environment variable and Pinecone MCP server to be configured.
argument-hint: query [q] index [indexName] namespace [ns] topK [k] reranker [rerankModel]
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# Pinecone Query Skill
Search for records in Pinecone integrated indexes using natural language text queries via the Pinecone MCP server.
## What is this skill for?
This skill provides a simple way to query **integrated indexes** (indexes with built-in Pinecone embedding models) using text queries. The MCP server automatically converts your text into embeddings and searches the index.
### Prerequisites
**Required:**
1. ✅ **Pinecone MCP server must be configured** - Check if MCP tools are available
2. ✅ **PINECONE_API_KEY environment variable must be set** - Get a free API key at https://app.pinecone.io/?sessionType=signup
3. ✅ **Index must be an integrated index** - Uses Pinecone embedding models (e.g., multilingual-e5-large, llama-text-embed-v2, pinecone-sparse-english-v0)
### When NOT to use this skill
**Use the CLI skill instead if:**
- ❌ Your index is a standard index (no integrated embedding model)