.codex-plugin/plugin.json

{
  "author": {
    "name": "Pinecone",
    "url": "https://www.pinecone.io"
  },
  "description": "Pinecone vector database integration for Codex. Streamline your Pinecone development with reusable skills for managing vector indexes, querying data, building RAG applications, and rapid prototyping. Includes the Pinecone MCP server for creating, describing, upserting, and searching indexes directly from Codex. Perfect for developers building semantic search, RAG applications, recommendation systems, and other vector-based applications with Pinecone.",
  "homepage": "https://www.pinecone.io",
  "interface": {
    "capabilities": [
      "Read",
      "Write"
    ],
    "category": "Developer Tools",
    "composerIcon": "./.codex-plugin/assets/composer-icon.png",
    "defaultPrompt": [
      "Use Pinecone to create a vector database with my pdfs",
      "Create a Pinecone assistant from the files in ./docs and ask it about authentication.",
      "Create a search engine for my website using the Documents API"
    ],
    "developerName": "Pinecone",
    "displayName": "Pinecone",
    "logo": "./.codex-plugin/assets/logo.png",
    "longDescription": "Use Pinecone with Codex through our skills and the Pinecone MCP Server. Enable Codex to access your vector databases via MCP, and build semantic search, knowledge layers, RAG, search engines, hybrid-search apps and more.",
    "privacyPolicyURL": "https://www.pinecone.io/privacy",
    "shortDescription": "Add knowledge to your AI app",
    "supportURL": "https://www.pinecone.io/contact/support/?_gl=1*1nge5or*_gcl_aw*R0NMLjE3ODg5ODM1MDIuQ2owS0NRandoNFRWQmhDV0FSSXNBRzBjem1wQUlreVhoaDMtOVo0R0pNZkw5TU5zM1AteUNJVTd0SGpLY21mRFFYRGtiaHFwR0NlbjZlTWFBcDFFRUFMd193Y0I.*_gcl_au*MTUxNDExMTMyMC4xNzgzNDUyMzQ2Li0uLS4xNzg0NzQzNTAxLjEzODM0NTUwNTkuMTc4OTc0NzgxNy4xNzg5Nzc1MDYy",
    "termsOfServiceURL": "https://www.pinecone.io/legal/master-subscription-agreement/",
    "websiteURL": "https://www.pinecone.io"
  },
  "keywords": [
    "pinecone",
    "semantic search",
    "retrieval",
    "vector search",
    "vector database",
    "retrieval augmented generation",
    "rag",
    "agentic rag",
    "sparse search",
    "assistant",
    "pinecone assistant",
    "rag chatbot",
    "full text search",
    "bm25",
    "hybrid search"
  ],
  "license": "MIT",
  "mcpServers": "./.mcp.json",
  "name": "pinecone",
  "repository": "https://github.com/pinecone-io/pinecone-codex-plugin",
  "requires_local_executor": true,
  "skills": "./skills/",
  "version": "1.0.1"
}