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Vectara MCP server

Official
by vectara

search_vectara

Execute a semantic search query using Vectara to retrieve contextually relevant results without generation. Provide a query, corpus keys, and API key to access matching search results from specified corpora.

Instructions

Run a semantic search query using Vectara, without generation.

Args:
    query: str, The user query to run - required.
    corpus_keys: list[str], List of Vectara corpus keys to use for the search - required. Please ask the user to provide one or more corpus keys. 
    api_key: str, The Vectara API key - required.
    n_sentences_before: int, Number of sentences before the answer to include in the context - optional, default is 2.
    n_sentences_after: int, Number of sentences after the answer to include in the context - optional, default is 2.
    lexical_interpolation: float, The amount of lexical interpolation to use - optional, default is 0.005.

Returns:
    The response from Vectara, including the matching search results.

Input Schema

NameRequiredDescriptionDefault
api_keyNo
corpus_keysNo
lexical_interpolationNo
n_sentences_afterNo
n_sentences_beforeNo
queryYes

Input Schema (JSON Schema)

{ "properties": { "api_key": { "default": "", "title": "Api Key", "type": "string" }, "corpus_keys": { "default": [], "items": { "type": "string" }, "title": "Corpus Keys", "type": "array" }, "lexical_interpolation": { "default": 0.005, "title": "Lexical Interpolation", "type": "number" }, "n_sentences_after": { "default": 2, "title": "N Sentences After", "type": "integer" }, "n_sentences_before": { "default": 2, "title": "N Sentences Before", "type": "integer" }, "query": { "title": "Query", "type": "string" } }, "required": [ "query" ], "title": "search_vectaraArguments", "type": "object" }

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