Expose Pinecone MCP tools for AI agents to discover and invoke.
npx skills add https://github.com/pinecone-io/gemini-cli-extension --skill mcp-pinecone-io
Please help me install this Agent Skill. Skill: mcp Source: https://github.com/pinecone-io/gemini-cli-extension/tree/main/skills/mcp Command: npx skills add https://github.com/pinecone-io/gemini-cli-extension --skill mcp-pinecone-io
Reference guide for Pinecone MCP server tools, detailing available commands, their purposes, and parameter expectations to help agents reason about tool usage.
Ask the MCP reference to enumerate all tools and explain how to use them.
High-intent search queries and answers about installing and using this skill.
Pinecone MCP server tools include list-indexes, describe-index, describe-index-stats, create-index-for-model, upsert-records, search-records, cascading-search, and rerank-documents. These tools enable agents to configure indexes, inject data, perform semantic search, and rerank results.
To upsert records, invoke the upsert-records tool provided by the Pinecone MCP reference. The tool requires specific parameters for data injection, which the reference details to ensure agents execute accurate and structured MCP tool invocations.
Yes, you can use the create-index-for-model tool to configure Pinecone indexes for specific models. The MCP reference provides structured guidance on the required and optional parameters needed to accurately execute this index configuration command.
The best way to perform semantic search and rerank documents is by invoking the search-records, cascading-search, and rerank-documents MCP tools. The reference guides agents on parameter expectations to ensure consistent and safe tool invocations.
Yes, the Pinecone MCP reference explicitly documents required and optional parameters for tools like list-indexes and describe-index. This parameter guidance helps AI agents reason about tool usage and ensures accurate, structured MCP invocations.
You use cascading-search or search-records when performing semantic search operations via the Pinecone MCP server. The reference catalog documents both tools and their parameter expectations to help agents select the correct command for their specific search use case.
patricio0312revConfigure Pinecone, Chroma, pgvector, and Qdrant vector databases for semantic search.
pinecone-ioSearch Pinecone indexes with natural language via MCP tools.
markus41Manage vector embeddings for semantic search across Pinecone, Weaviate, Chroma, and pgvector.
sheawinklerIndex embeddings and metadata for on-disk vector search.
