mcp-google-agent-platform-docs

MCP server providing Google AI platform documentation to AI agents.

Part of OpenGerwin MCP Servers

What is this?

An MCP (Model Context Protocol) server that gives AI agents direct access to Google's AI platform documentation — both the current Gemini Enterprise Agent Platform (GEAP) and the legacy Vertex AI Generative AI docs.

Instead of hallucinating API details, your AI assistant can look up the actual documentation in real-time.

Features

• 🔍 Full-text search across 3400+ documentation pages
• 📄 On-demand fetching — pages are downloaded and cached as you need them
• 🗂️ Dual source — current GEAP + legacy Vertex AI documentation
• ⚡ Smart caching — 72-hour TTL, stale fallback on network errors
• 🗺️ Auto-discovery — new pages found via sitemap scanning (weekly)
• 🧩 Plug & play — works with Claude Desktop, Cursor, VS Code, any MCP client

Quick Start

Install

# Using pip
pip install mcp-google-agent-platform-docs

# Using uv (recommended)
uv pip install mcp-google-agent-platform-docs

Configure Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "google-agent-platform-docs": {
      "command": "mcp-google-agent-platform-docs"
    }
  }
}

Configure Antigravity (Google)

Add to ~/.gemini/antigravity/mcp_config.json:

{
  "mcpServers": {
    "google-agent-platform-docs": {
      "command": "uv",
      "args": [
        "--directory",
        "/path/to/mcp-google-agent-platform-docs",
        "run",
        "mcp-google-agent-platform-docs"
      ]
    }
  }
}

Configure Cursor / VS Code

Add to your MCP settings:

{
  "mcpServers": {
    "google-agent-platform-docs": {
      "command": "mcp-google-agent-platform-docs",
      "transport": "stdio"
    }
  }
}

Tools

search_docs

Search documentation by keywords.

search_docs("Memory Bank setup", source="geap")
search_docs("function calling", source="vertex-ai")

get_doc

Get full content of a specific page.

get_doc("scale/memory-bank/setup", source="geap")
get_doc("multimodal/function-calling", source="vertex-ai")

list_sections

Browse documentation structure.

list_sections(source="geap")

list_models

Quick reference for all available AI models (Gemini, Imagen, Veo, Claude, etc.).

list_models()

Documentation Sources

| Source ID | Platform | Pages | Status | |---|---|---|---| | geap | Gemini Enterprise Agent Platform | 2300+ | Primary (current) | | vertex-ai | Vertex AI Generative AI | 1100+ | Legacy (archive) |

GEAP Sections

• Agent Studio — Visual agent builder
• Agents → Build — Runtime, ADK, Agent Garden, RAG Engine
• Agents → Scale — Sessions, Memory Bank, Code Execution
• Agents → Govern — Policies, Agent Gateway, Model Armor
• Agents → Optimize — Observability, Evaluation, Quality Alerts
• Models — Gemini, Imagen, Veo, Lyria, Partners, Open Models
• Notebooks — Jupyter tutorials

Configuration

Environment variables for customization:

| Variable | Default | Description | |---|---|---| | MCP_DOCS_CACHE_DIR | ~/.cache/mcp-google-agent-platform-docs | Cache directory | | MCP_DOCS_CONTENT_TTL | 72 | Page cache TTL (hours) | | MCP_DOCS_STRUCTURE_TTL | 7 | Structure cache TTL (days) | | MCP_DOCS_DEFAULT_SOURCE | geap | Default documentation source | | MCP_DOCS_HTTP_TIMEOUT | 30 | HTTP timeout (seconds) |

Development

# Clone
git clone https://github.com/OpenGerwin/mcp-google-agent-platform-docs.git
cd mcp-google-agent-platform-docs

# Install dependencies
uv sync

# Run server locally
uv run mcp-google-agent-platform-docs

# Test with MCP Inspector
uv run mcp dev src/mcp_google_agent_platform_docs/server.py

Architecture

mcp-google-agent-platform-docs/
├── sources/                    # YAML source configurations
│   ├── geap.yaml               # GEAP (primary)
│   └── vertex-ai.yaml          # Vertex AI (legacy)
├── src/mcp_google_agent_platform_docs/
│   ├── server.py               # FastMCP server + 4 tools
│   ├── source.py               # Source model (YAML loader)
│   ├── fetcher.py              # HTML → Markdown converter
│   ├── cache.py                # TTL cache manager
│   ├── discovery.py            # Sitemap-based page discovery
│   ├── search.py               # TF-IDF search engine
│   └── config.py               # Global configuration
└── tests/

License

MIT — see LICENSE.

Part of OpenGerwin MCP Servers