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Connect AI assistants to Discovery Engine for search, RAG, and datastore management.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Gemini Enterprise MCP Server" yet — see the docs or source repo.
Use the Gemini Enterprise MCP Server to connect to Google Cloud Discovery Engine and enable semantic search for my internal knowledge base. First explain the required connection setup, then show an example query for "how to reset employee VPN".
Provides setup steps, required configuration details, and a sample semantic search call.
Using the Gemini Enterprise MCP Server, build a conversational RAG assistant on top of Discovery Engine with product documentation as the data source. Show the implementation approach, retrieval-QA flow, and an example response structure for the question "What access controls does the enterprise edition support?"
Returns a RAG architecture outline, QA flow design, and an example response format for a real query.
Show how to manage Discovery Engine datastores, documents, and configurations through the Gemini Enterprise MCP Server, including typical actions for creating a datastore, updating documents, and checking index configuration status.
Provides step-by-step guidance or sample calls for common administration tasks to maintain the retrieval system.
Look up Gemini API docs and get ready-to-use code snippets fast.
Query Gemini with Google Search grounding for current answers and source links.
Connect Gemini and OpenAI CLIs for unified AI-driven development workflows.
Manage Gemini file-search knowledge stores and run RAG-based document queries.
Use Gemini CLI in Claude Desktop or Code via Google login.
Access Gemini through MCP clients for Q&A, generation, and development workflows.