[
  {
    "id": "pinecone-docs-1",
    "tier": "claimed-docs",
    "url": "https://docs.pinecone.io",
    "excerpt": "Build semantic search and knowledge retrieval into your agent or app",
    "fetchedAt": "2026-09-04T22:07:59.938Z"
  },
  {
    "id": "pinecone-docs-2",
    "tier": "claimed-docs",
    "url": "https://docs.pinecone.io",
    "excerpt": "Create an AI assistant that answers questions about your proprietary data",
    "fetchedAt": "2026-09-04T22:07:59.938Z"
  },
  {
    "id": "pinecone-docs-3",
    "tier": "claimed-docs",
    "url": "https://docs.pinecone.io",
    "excerpt": "Compile your data into a context and query it for grounded, cited answers",
    "fetchedAt": "2026-09-04T22:07:59.938Z"
  },
  {
    "id": "pinecone-docs-4",
    "tier": "claimed-docs",
    "url": "https://docs.pinecone.io",
    "excerpt": "Publish a no-code knowledge app from a template (public preview)",
    "fetchedAt": "2026-09-04T22:07:59.938Z"
  },
  {
    "id": "pinecone-docs-5",
    "tier": "claimed-docs",
    "url": "https://docs.pinecone.io",
    "excerpt": "Use Pinecone with Claude Code, Gemini CLI, Cursor, and other agentic tools",
    "fetchedAt": "2026-09-04T22:07:59.938Z"
  },
  {
    "id": "pinecone-docs-6",
    "tier": "claimed-docs",
    "url": "https://docs.pinecone.io",
    "excerpt": "Connect any MCP-compatible agent to Pinecone for search and index management",
    "fetchedAt": "2026-09-04T22:07:59.938Z"
  },
  {
    "id": "pinecone-docs-7",
    "tier": "claimed-docs",
    "url": "https://docs.pinecone.io/guides/index-data/indexing-overview",
    "excerpt": "A single index can serve full-text search (BM25 with Lucene queries), semantic search, and sparse-vector search together, often covering what previously required two indexes.",
    "fetchedAt": "2026-09-04T22:07:59.938Z"
  },
  {
    "id": "pinecone-docs-8",
    "tier": "claimed-docs",
    "url": "https://docs.pinecone.io/guides/index-data/indexing-overview",
    "excerpt": "When you search, you rank results via `score_by`: `text` (BM25), `query_string` (Lucene), `dense_vector`, or `sparse_vector`.",
    "fetchedAt": "2026-09-04T22:07:59.938Z"
  },
  {
    "id": "pinecone-docs-9",
    "tier": "claimed-docs",
    "url": "https://docs.pinecone.io/guides/search/hybrid-search",
    "excerpt": "Hybrid search combines a keyword signal with a semantic signal so a single query benefits from both.",
    "fetchedAt": "2026-09-04T22:07:59.938Z"
  },
  {
    "id": "pinecone-docs-10",
    "tier": "claimed-docs",
    "url": "https://docs.pinecone.io/guides/search/filter-by-metadata",
    "excerpt": "you can then include a metadata filter to limit the search to records matching the filter expression",
    "fetchedAt": "2026-09-04T22:07:59.938Z"
  },
  {
    "id": "pinecone-docs-11",
    "tier": "claimed-docs",
    "url": "https://docs.pinecone.io/guides/index-data/implement-multitenancy",
    "excerpt": "Implement multitenancy in Pinecone using a **serverless index with one namespace per tenant**.",
    "fetchedAt": "2026-09-04T22:07:59.938Z"
  },
  {
    "id": "pinecone-docs-12",
    "tier": "claimed-docs",
    "url": "https://docs.pinecone.io/guides/manage-data/back-up-an-index",
    "excerpt": "Create backups of serverless indexes to protect data, copy indexes, or experiment with configurations using the Pinecone SDK, API, or console.",
    "fetchedAt": "2026-09-04T22:07:59.938Z"
  },
  {
    "id": "pinecone-docs-13",
    "tier": "claimed-docs",
    "url": "https://docs.pinecone.io/guides/production/security-overview",
    "excerpt": "You can manage API key permissions in the Pinecone console... Pinecone uses role-based access controls (RBAC) to manage access to resources.",
    "fetchedAt": "2026-09-04T22:07:59.938Z"
  },
  {
    "id": "pinecone-docs-14",
    "tier": "claimed-docs",
    "url": "https://docs.pinecone.io/reference/api/introduction",
    "excerpt": "Use the Inference API to generate vector embeddings and rerank results using embedding models and reranking models hosted on Pinecone's infrastructure.",
    "fetchedAt": "2026-09-04T22:07:59.938Z"
  },
  {
    "id": "pinecone-docs-15",
    "tier": "claimed-docs",
    "url": "https://docs.pinecone.io/guides/operations/mcp-server",
    "excerpt": "Using the MCP server, agents can search Pinecone documentation, manage indexes, upsert data, and query indexes for relevant information.",
    "fetchedAt": "2026-09-04T22:07:59.938Z"
  },
  {
    "id": "pinecone-docs-16",
    "tier": "claimed-docs",
    "url": "https://www.pinecone.io",
    "excerpt": "Monitor performance, explore your data, and manage indexes from a clean, fast console — or stay in the terminal. Your call.",
    "fetchedAt": "2026-09-04T22:07:59.938Z"
  },
  {
    "id": "pinecone-docs-17",
    "tier": "claimed-docs",
    "url": "https://docs.pinecone.io/guides/index-data/indexing-overview",
    "excerpt": "A single index can serve full-text search (BM25 with Lucene queries), semantic search, and sparse-vector search together",
    "fetchedAt": "2026-09-04T22:09:42.087Z"
  },
  {
    "id": "pinecone-docs-18",
    "tier": "claimed-docs",
    "url": "https://docs.pinecone.io/guides/index-data/indexing-overview",
    "excerpt": "Full-text search is BM25 token matching with Lucene query syntax over text fields in your schema... No model required",
    "fetchedAt": "2026-09-04T22:09:42.087Z"
  },
  {
    "id": "pinecone-docs-19",
    "tier": "claimed-docs",
    "url": "https://docs.pinecone.io/guides/index-data/implement-multitenancy",
    "excerpt": "Implement multitenancy in Pinecone using a serverless index with one namespace per tenant.",
    "fetchedAt": "2026-09-04T22:09:42.087Z"
  },
  {
    "id": "pinecone-docs-20",
    "tier": "claimed-docs",
    "url": "https://docs.pinecone.io/guides/manage-data/back-up-an-index",
    "excerpt": "Create backups of serverless indexes to protect data, copy indexes, or experiment with configurations",
    "fetchedAt": "2026-09-04T22:09:42.087Z"
  },
  {
    "id": "pinecone-docs-21",
    "tier": "claimed-docs",
    "url": "https://docs.pinecone.io/guides/production/security-overview",
    "excerpt": "SSO allows organizations to manage their teams’ access to Pinecone through their identity management solution.",
    "fetchedAt": "2026-09-04T22:09:42.087Z"
  },
  {
    "id": "pinecone-docs-22",
    "tier": "claimed-docs",
    "url": "https://docs.pinecone.io/guides/production/security-overview",
    "excerpt": "Audit logs provide a detailed record of user and API actions that occur within Pinecone.",
    "fetchedAt": "2026-09-04T22:09:42.087Z"
  },
  {
    "id": "pinecone-docs-23",
    "tier": "claimed-docs",
    "url": "https://docs.pinecone.io/reference/api/introduction",
    "excerpt": "Use the Inference API to generate vector embeddings and rerank results using embedding models and reranking models hosted on Pinecone’s infrastructure.",
    "fetchedAt": "2026-09-04T22:09:42.087Z"
  },
  {
    "id": "pinecone-docs-24",
    "tier": "claimed-docs",
    "url": "https://docs.pinecone.io/guides/operations/mcp-server",
    "excerpt": "agents can search Pinecone documentation, manage indexes, upsert data, and query indexes for relevant information",
    "fetchedAt": "2026-09-04T22:09:42.087Z"
  },
  {
    "id": "pinecone-docs-25",
    "tier": "claimed-docs",
    "url": "https://www.pinecone.io",
    "excerpt": "Monitor performance, explore your data, and manage indexes from a clean, fast console — or stay in the terminal.",
    "fetchedAt": "2026-09-04T22:09:42.087Z"
  },
  {
    "id": "pinecone-docs-26",
    "tier": "claimed-docs",
    "url": "https://www.pinecone.io",
    "excerpt": "$ claude plugin install pinecone",
    "fetchedAt": "2026-09-04T22:09:42.087Z"
  },
  {
    "id": "pinecone-docs-27",
    "tier": "claimed-docs",
    "url": "https://docs.pinecone.io/guides/search/hybrid-search",
    "excerpt": "Combine keyword and semantic retrieval in Pinecone with a text-match filter on a dense search, or by fusing separate searches with reciprocal rank fusion.",
    "fetchedAt": "2026-09-04T22:11:17.924Z"
  },
  {
    "id": "pinecone-docs-28",
    "tier": "claimed-docs",
    "url": "https://docs.pinecone.io/guides/search/filter-by-metadata",
    "excerpt": "Narrow Pinecone search results by adding metadata filter expressions to your query, using operators like eq,eq, eq,in, gt,andgt, and gt,andand for precise retrieval.",
    "fetchedAt": "2026-09-04T22:11:17.924Z"
  },
  {
    "id": "pinecone-docs-29",
    "tier": "claimed-docs",
    "url": "https://docs.pinecone.io/guides/production/security-overview",
    "excerpt": "Pinecone uses role-based access controls (RBAC) to manage access to resources.",
    "fetchedAt": "2026-09-04T22:11:17.924Z"
  },
  {
    "id": "pinecone-docs-30",
    "tier": "claimed-docs",
    "url": "https://docs.pinecone.io/guides/operations/mcp-server",
    "excerpt": "Connect AI agents to Pinecone through the MCP server to search docs, manage indexes, and query data from Claude, Cursor, Antigravity, or Claude Code.",
    "fetchedAt": "2026-09-04T22:12:51.191Z"
  },
  {
    "id": "pinecone-docs-31",
    "tier": "claimed-docs",
    "url": "https://docs.pinecone.io/guides/index-data/indexing-overview",
    "excerpt": "When you search, you rank results via score_by: text (BM25), query_string (Lucene), dense_vector, or sparse_vector.",
    "fetchedAt": "2026-09-04T22:12:51.191Z"
  },
  {
    "id": "pinecone-docs-32",
    "tier": "claimed-docs",
    "url": "https://docs.pinecone.io/guides/search/filter-by-metadata",
    "excerpt": "Narrow Pinecone search results by adding metadata filter expressions to your query, using operators like eq, in, gt, and gt, and for precise retrieval.",
    "fetchedAt": "2026-09-04T22:12:51.191Z"
  },
  {
    "id": "pinecone-docs-33",
    "tier": "claimed-docs",
    "url": "https://docs.pinecone.io/guides/index-data/implement-multitenancy",
    "excerpt": "This page shows you how to implement multitenancy in Pinecone using a serverless index with one namespace per tenant.",
    "fetchedAt": "2026-09-04T22:12:51.191Z"
  },
  {
    "id": "pinecone-docs-34",
    "tier": "claimed-docs",
    "url": "https://docs.pinecone.io/guides/production/security-overview",
    "excerpt": "Overview of Pinecone security features for production: API keys, SSO, service accounts, audit logs, CMEK encryption, backups, and Private Endpoints.",
    "fetchedAt": "2026-09-04T22:12:51.191Z"
  },
  {
    "id": "pinecone-comm-1",
    "tier": "community",
    "url": "https://news.ycombinator.com/item?id=35729816",
    "excerpt": "Happy for them, has been a very smooth developer experience using Pinecone and I think there is more than meets the eye with the combined keyword+vector search and handling of filtering.",
    "fetchedAt": "2026-09-04T22:14:14.809Z"
  },
  {
    "id": "pinecone-comm-2",
    "tier": "community",
    "url": "https://news.ycombinator.com/item?id=35729816",
    "excerpt": "I was using pinecone before installing pgvector in Postgres. Pinecone works and all but having the vectors in Postgres resulted in an explosion of use for us. Full relational queries with where clauses and order by etc AND vector embeddings is wicked.",
    "fetchedAt": "2026-09-04T22:14:14.809Z"
  },
  {
    "id": "pinecone-comm-3",
    "tier": "community",
    "url": "https://news.ycombinator.com/item?id=35729816",
    "excerpt": "They're so hot right now that you can't even signup for a starter account... It's a really easy DB to use for people with no idea about vector DBs, etc. It \"just works\".",
    "fetchedAt": "2026-09-04T22:14:14.809Z"
  },
  {
    "id": "pinecone-comm-4",
    "tier": "community",
    "url": "https://news.ycombinator.com/item?id=35729816",
    "excerpt": "I'm still surprised by their generous free tier, I have a database of 300k embeddings on Pinecone and it's only 10% full by their metrics... it would take crazy amounts of traffic or a ton more data for me to convert from their free tier.",
    "fetchedAt": "2026-09-04T22:14:14.809Z"
  },
  {
    "id": "pinecone-comm-5",
    "tier": "community",
    "url": "https://news.ycombinator.com/item?id=35729816",
    "excerpt": "I honestly hope they use it to improve their documentation... I couldn't honestly figure out how to use it... Ended up just sticking with Algolia, since we had them in place for Search anyway.",
    "fetchedAt": "2026-09-04T22:14:14.809Z"
  },
  {
    "id": "pinecone-comm-6",
    "tier": "community",
    "url": "https://news.ycombinator.com/item?id=35729816",
    "excerpt": "Perfect example of AI gold rush nonsense. Pinecone has zero moat and quite a few free alternatives (Faiss, Weviate, pg-vector).",
    "fetchedAt": "2026-09-04T22:14:14.809Z"
  },
  {
    "id": "pinecone-comm-7",
    "tier": "community",
    "url": "https://hn.algolia.com/api/v1/items/40646276",
    "excerpt": "After trying a number of different options (Pinecone, ChromaDB, FAISS + memory stores), I felt like pgvector offered the best value and project maturity. Performance was my biggest concern, though much of that was based on blog posts that might be FUD rather than real benchmarks.",
    "fetchedAt": "2026-09-04T22:14:14.809Z"
  },
  {
    "id": "pinecone-comm-8",
    "tier": "community",
    "url": "https://hn.algolia.com/api/v1/items/41007624",
    "excerpt": "There was a long time that pgvector only had basic similarity algorithms and not HNSW but pinecone did. That plus being 'fully managed' made it a super compelling product. Nowadays, much less so.",
    "fetchedAt": "2026-09-04T22:14:14.809Z"
  },
  {
    "id": "pinecone-comm-9",
    "tier": "community",
    "url": "https://news.ycombinator.com/item?id=37050532",
    "excerpt": "Querying records in Pinecone can sometimes give you the right results, it can also be a bit unpredictable, depending on what and how you query.",
    "fetchedAt": "2026-09-04T22:14:14.809Z"
  },
  {
    "id": "pinecone-comm-10",
    "tier": "community",
    "url": "https://news.ycombinator.com/item?id=37050532",
    "excerpt": "When there are so many awesome FOSS vector databases available, I wonder what motivated the airbyte team to use Pinecone, the one database that is anti-FOSS?",
    "fetchedAt": "2026-09-04T22:14:14.809Z"
  },
  {
    "id": "pinecone-probe-1",
    "tier": "probe",
    "url": "https://docs.pinecone.io/llms.txt",
    "excerpt": "PROBE llms.txt: HTTP 200 at https://docs.pinecone.io/llms.txt # Pinecone Docs\n\n> Official Pinecone documentation for the vector database, Assistant, inference APIs, SDKs, and buildin",
    "fetchedAt": "2026-09-04T22:15:07.392Z"
  },
  {
    "id": "pinecone-probe-2",
    "tier": "probe",
    "url": "https://docs.pinecone.io/openapi.json",
    "excerpt": "PROBE openapi: all candidate paths 404 (https://docs.pinecone.io/openapi.json, https://docs.pinecone.io/swagger.json, https://docs.pinecone.io/api/openapi.json, https://docs.pinecone.io/.well-known/openapi.json)",
    "fetchedAt": "2026-09-04T22:15:07.392Z"
  },
  {
    "id": "pinecone-probe-3",
    "tier": "probe",
    "url": "https://docs.pinecone.io/guides/operations/mcp-server",
    "excerpt": "official MCP server documented at https://docs.pinecone.io/guides/operations/mcp-server",
    "fetchedAt": "2026-09-04T22:15:07.392Z"
  }
]