Pinecone
Pinecone enables efficient semantic search by indexing and querying vector embeddings, quickly finding similar content for applications like recommendation & knowledge retrieval.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add pinecone npx -- -y @trustedskills/pinecone
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"pinecone": {
"command": "npx",
"args": [
"-y",
"@trustedskills/pinecone"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
The Pinecone skill enables AI agents to interact with vector databases, allowing efficient storage and retrieval of high-dimensional data. It supports operations like adding vectors, querying nearest neighbors, and managing indexes.
When to use it
- To build recommendation systems that rely on similarity searches between items.
- For natural language processing tasks where semantic search is required.
- When developing AI applications that need fast access to large datasets using vector embeddings.
Key capabilities
- Integration with Pinecone's API for managing vectors and indexes
- Support for efficient nearest neighbor queries
- Scalable storage of high-dimensional data
Example prompts
- "Find the three most similar documents to this query using the Pinecone database."
- "Add these new text embeddings to the Pinecone index for later retrieval."
- "Query the Pinecone vector store for items closest to the given embedding."
Tips & gotchas
- Ensure you have a valid Pinecone API key and project set up before using this skill.
- Be mindful of data size limits and cost implications when working with large datasets.
Tags
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Security Audits
| Gen Agent Trust Hub | Pass |
| Socket | Pass |
| Snyk | Pass |
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