Pinecone Developer MCP

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search-records

Search an index for records similar to query text, specifying namespace, top results, and optional filters or reranking models for enhanced relevance in Pinecone Developer MCP.

Instructions

Search an index for records that are similar to the query text

Input Schema

NameRequiredDescriptionDefault
nameYesThe index to search.
namespaceYesThe namespace to search.
queryYesA query to search for records.
rerankNoReranking can help determine which of the returned records are most relevant. When reranking, use a "query" with a "topK" that returns more results than you need; then use "rerank" to select the most relevant "topN" results.

Input Schema (JSON Schema)

{ "$schema": "http://json-schema.org/draft-07/schema#", "additionalProperties": false, "properties": { "name": { "description": "The index to search.", "type": "string" }, "namespace": { "description": "The namespace to search.", "type": "string" }, "query": { "additionalProperties": false, "description": "A query to search for records.", "properties": { "filter": { "description": "A filter can be used to narrow down results. Use the syntax of\n MongoDB's query and projection operators: $eq, $ne, $gt, $gte, $lt,\n $lte, $in, $nin, $exists, $and, $or. Make sure the records in the index\n contain the fields that you are filtering on." }, "inputs": { "additionalProperties": false, "properties": { "text": { "description": "The text to search for.", "type": "string" } }, "required": [ "text" ], "type": "object" }, "topK": { "description": "The number of results to return.", "type": "number" } }, "required": [ "topK", "inputs" ], "type": "object" }, "rerank": { "additionalProperties": false, "description": "Reranking can help determine which of the returned records are most\n relevant. When reranking, use a \"query\" with a \"topK\" that returns more\n results than you need; then use \"rerank\" to select the most relevant\n \"topN\" results.", "properties": { "model": { "description": "Choose a reranking model:\n- \"cohere-rerank-3.5\" is Cohere's leading reranking model, balancing performance\nand latency for a wide range of enterprise search applications.\n- \"bge-reranker-v2-m3\" is a high-performance, multilingual reranking model that\nworks well on messy data and short queries expected to return medium-length\npassages of text (1-2 paragraphs).\n- \"pinecone-rerank-v0\" is a state of the art reranking model that out-performs\ncompetitors on widely accepted benchmarks. It can handle chunks up to 512 tokens\n(1-2 paragraphs).", "enum": [ "cohere-rerank-3.5", "bge-reranker-v2-m3", "pinecone-rerank-v0" ], "type": "string" }, "query": { "description": "An optional query to rerank documents against. If not specified, the\n same query will be used for both the initial search and the reranking.", "type": "string" }, "rankFields": { "description": "The fields to rerank on. This should include the field name specified\n in the index's \"fieldMap\". The \"bge-reranker-v2-m3\" and\n \"pinecone-rerank-v0\" models support only a single rerank field.\n \"cohere-rerank-3.5\" supports multiple rerank fields.", "items": { "type": "string" }, "type": "array" }, "topN": { "description": "The number of results to return after reranking. Must be less than or\n equal to the value of \"query.topK\".", "type": "number" } }, "required": [ "model", "rankFields" ], "type": "object" } }, "required": [ "name", "namespace", "query" ], "type": "object" }

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