Answer natural language queries by combining Vertex AI's Gemini model with real-time Google Search results, delivering accurate and up-to-date information on demand.
Retrieves answers to natural language queries using Google Search, processes them with Vertex AI models, and saves the results to a specified file path for easy access and storage.
Saves precise code snippets or concise answers from official documentation to a specified file, using a Vertex AI model with Google Search for technical queries. Requires topic, query, and output path.
Generate detailed explanations for software-related queries by synthesizing insights from official documentation, using Vertex AI's Gemini model and web search grounding for accuracy and context.
Provides answers to natural language queries using Vertex AI's internal knowledge, without web search. Input a query string to extract precise information directly from the model.
Implementation of Model Context Protocol (MCP) server that provides tools for accessing Google Cloud's Vertex AI Gemini models, supporting features like web search grounding and direct knowledge answering for coding assistance and general queries.
A server that enables document searching using Vertex AI with Gemini grounding, improving search results by grounding responses in private data stored in Vertex AI Datastore.
MCP Server for Google Cloud Healthcare API enables Agentic AI for a variety of FHIR-based digital health solutions, from smarter clinical workflows for Health Systems to Pre-Auth frameworks for Payers!