MARKET RESEARCH

CodexPluginStats: Codex plugin directory

Codex Plugin Stats: discover plugins, explore their skills and track catalog growth and observed changes.

Explore 5,319 plugins across 14 categories.

All plugins 7

1–7 of 7

All query words must match. Use quotes for an exact phrase. Matches include publisher text, keywords and attributed research.

Discover Codex plugins by task and category
Plugin / developer	Category	Follow
ZillizZillizWork with Zilliz Cloud and Milvus vector databases using the zilliz-cli. Publisher subtitle Manage Zilliz vector databases Show in context → 2 more matching sources Publisher keywords · listing zilliz milvus vector-database semantic-search rag Show in context → Publisher description Work with Zilliz Cloud and Milvus vector databases using the zilliz-cli. Show in context →	Developer ToolsVersion 1.4.4	View details →
Azure Cosmos DBAzure Cosmos DBOfficial Codex plugin for Azure Cosmos DB (NoSQL). Best practice skills for data modeling, queries, indexing, vector search, security, an... Publisher keywords · listing azure cosmosdb cosmos-db nosql database vector-search agent-skills Show in context → 2 more matching sources Publisher description …odex plugin for Azure Cosmos DB (NoSQL). Best practice skills for data modeling, queries, indexing, vector search, security, and more. Show in context → Publisher full description …on client, bulk operations, direct mode), indexing strategies (composite, spatial, exclude unused), vector search (DiskANN, flat, quantized flat), full-text search (BM25, hybrid queries), global distribution (multi-region writes, conflict resolution), security (Entra ID, managed identity, RBAC, netw… Show in context →	Data & AnalyticsVersion 1.2.0	View details →
PineconePineconePinecone vector database integration for Codex. Streamline your Pinecone development with reusable skills for managing vector indexes, qu... Publisher keywords · listing 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 Show in context → 2 more matching sources Publisher 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 Pin… Show in context → Publisher full description 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. Show in context →	Developer ToolsVersion 1.0.1	View details →
RedisRedisRedis development best practices for data modeling, search, caching, connections, clustering, security, observability, and agent memory Publisher keywords · listing redis database caching vector-search performance best-practices Show in context →	Developer ToolsVersion 1.4.0	View details →
AWS Data AnalyticsAmazon Web Services Publisher description …th S3 Tables, AWS Glue, and Athena. Covers managed Iceberg tables on S3 Tables, ingestion from JDBC databases, Amazon Redshift, Snowflake, BigQuery, and DynamoDB, AWS Glue Data Catalog inventory and asset discovery, federated Athena queries, and vector storage and semantic search on Amazon S3 Vectors. Show in context →	Data & AnalyticsVersion 1.0.0	View details →
Upstash RedisUpstash Publisher description …s from ChatGPT through the hosted Upstash MCP server (OAuth on first use): create and inspect Redis databases and run commands on them, publish QStash messages and manage schedules, build Vector and Search indexes, and drive Box sandboxes and Blob storage. Credentials stay on the server and are returned only when you ask for them. Show in context →	Developer ToolsVersion 1.2.1	View details →
VATESSTANDOUT Inc. Publisher description …anguage and get answers grounded in your material, traceable to the exact source entry. There is no vector database and no embedding step — knowledge is stored as plain, human-readable text and interpreted at the moment you ask, so updates take effect instantly and every answer can be audited. Show in context →	ProductivityVersion 1.0.0	View details →