Vertex AI Search

Vertex AI Search MCP Connector for Claude

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Search across your enterprise data using Google's semantic search and generative AI grounding.

7 tools Official Updated Jun 28, 2026 Official Vinkius Partner

Connect your Vertex AI Search account to any AI agent and harness the power of Google's semantic search technology on your own enterprise data through natural conversation.

What you can do

  • Semantic Search — Perform high-quality semantic searches across documents with AI-powered relevance and accuracy
  • Grounded Answers — Get direct, natural language answers grounded in your private document collection for reliable Q&A
  • Data Stores — List and browse your enterprise data stores and search engines to manage your searchable datasets
  • Document Discovery — Browse and list indexed documents within your data store branches directly from your agent
  • Personalized Recommendations — Retrieve intelligent recommendations based on user interaction events and patterns
  • Search Engines — View and manage high-level search applications configured for specific business use cases

How it works

  1. Subscribe to this server
  2. Enter your Google Cloud Project ID, Location, and Access Token
  3. Start querying your enterprise data through Claude, Cursor, or any MCP-compatible client

No more manual digging through complex documentation systems. Your AI agent becomes your enterprise knowledge expert.

Who is this for?

  • Enterprise Developers — build grounded AI applications using internal documentation and knowledge bases without manual indexing
  • Knowledge Managers — quickly surface relevant information from massive document repositories through simple conversation
  • Data Scientists — rapidly test and refine search relevance and generative grounding configurations
  • Product Teams — implement personalized recommendations and AI-powered search features with minimal friction
enterprise-searchgroundingsemantic-searchgenerative-ainatural-language-processingdata-retrieval

7 tools expose this connector's capabilities to your AI agent.

get_grounded_answer

Returns a natural language response based on your private data. Retrieves an AI-generated answer grounded in the documents of a data store

get_datastore_details

Retrieves configuration and metadata for a specific data store

list_data_stores

Lists all data stores in the Vertex AI Search collection

list_datastore_documents

Provide data store and branch IDs. Lists all indexed documents within a specific data store branch

list_search_engines

Lists all search engines configured in the collection

get_recommendations

Provide a data store ID and user event data as a JSON object. Retrieves personalized recommendations based on user events

search_documents

Provide a data store ID and the query text. Performs a search query across documents in a specific data store

See how to talk to your AI agent using Vertex AI Search.

List all my available data stores in Vertex AI Search.

I found 3 data stores: 'documentation-v1' (ID: doc-123), 'hr-policies' (ID: hr-456), and 'product-catalog' (ID: prod-789). Which one would you like to search through?

Based on our documentation, what is our remote work policy?

Grounded in the 'hr-policies' data store: Our remote work policy allows for up to 3 days of work from home per week, provided there is prior alignment with the team manager. Employees must ensure a stable internet connection and maintain core working hours. Would you like me to pull the full document?

Search the product catalog for 'blue wireless headphones'.

I found several matches in 'product-catalog': 1. 'CloudBass Pro Blue' (In Stock), 2. 'SkyBuds v2 Azure' (Limited Stock), and 3. 'Oceanic Beats Wireless' (Discontinued). I can provide more details on features or pricing for any of these.

Yes. Using the `get_grounded_answer` tool, your AI agent can process a natural language question and return a precise answer based specifically on the content within your Vertex AI Search data stores. This grounding ensures high accuracy and reduces hallucinations by sticking to your private data as the source of truth.

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