Search Google AI platform documentation for topics like function calling, Agent Development Kit, or Gemini Pro. Returns matching pages with titles, paths, and excerpts. Supports GEAP and Vertex AI sources. Use get_doc to read full content.
MIT
737,956 tools. Updated 2026-11-02 22:34
"Google Vertex AI Platform" matching MCP tools:
- Find Google Cloud Platform services and documentation by searching local mappings, official websites, and API repositories to identify relevant GCP tools for specific use cases.MIT
- List available compute backends including local GPU, Vertex AI, and Ollama, along with their models and latency.MIT
- Delete a specific file uploaded to the Gemini API by providing its unique file name (e.g., 'files/abc123xyz'). Returns a success confirmation upon deletion. Works exclusively with Google AI Studio API keys.MIT
- List all AI models on Google's platform, organized by family for quick reference. Includes Google models (Gemini, Imagen), partners (Claude, Grok), and open models (DeepSeek, Qwen).MIT
- 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.MIT
Matching MCP Servers
- AlicenseAqualityCmaintenanceAbout MCP server for Google Agent Platform Docs — Google AI + Vertex AI. 3400+ pages searchable by AI agents.41MIT
- AlicenseNot gradedqualityCmaintenanceEnables integration with Google Cloud Vertex AI Search for enterprise search capabilities through a stdio-based MCP server.MIT
Matching MCP Connectors
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- Analyzes code snippets against official documentation to identify bugs, performance issues, and security vulnerabilities. Uses Google Search and Vertex AI to compare code with best practices.MIT
- 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.MIT
- Fetch full documentation page content from Google Agent Platform or Vertex AI docs. Provide the page path and optional source to get complete markdown content, retrieved live if not cached.MIT
- Proxy Gemini (Vertex AI) completions with OpenTelemetry tracing. Returns the answer along with trace and span IDs for observability.MIT
- Reports which credential source nanobanana-mcp uses—Gemini API key, Vertex AI Express Mode, or ADC—without exposing secrets, and shows basic runtime details to debug setup.MIT
- Generate images from text prompts using Google Vertex AI Gemini models, with selectable model tiers and options for aspect ratio, output format, and file saving.MIT
- 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.MIT
- Retrieve metadata for a specific file uploaded to the Gemini API using its unique file name. Designed for use with Google AI Studio API keys within the MCP Gemini Server framework.MIT
- List all documentation sections with descriptions and page counts from Google Agent Platform or Vertex AI sources, providing a structured overview.MIT
- Starts an automated prompt optimization job on Vertex AI using a dataset and configurable metrics. Provide a config file in GCS and choose between VAPO or Gemini Nano methods.Apache 2.0
- Answers natural language queries by combining the Gemini model with live Google Search results to provide current information.MIT
- Authenticate with Google OAuth to access a secure LLM gateway that runs Gemini completions for verified users.MIT
- Run prompts through a LangChain (system + human) chain using Gemini on Vertex AI, with optional LangSmith tracing for observability.MIT
- Analyze images with a multimodal prompt to answer questions or follow instructions about visual content. Provide an image path and prompt to get image-based insights via Vertex AI.MIT
- Assign vertex weights to a named vertex group by specifying vertex indices. Choose replace, add, or subtract mode to adjust weights for precise rigging.Apache 2.0